IR-Datasets Integration

Datamaestro-text provides an interface to the ir-datasets library, giving access to hundreds of IR benchmarks through a unified API.

Install ir-datasets:

pip install ir-datasets

Usage:

from datamaestro import prepare_dataset

# Load any ir-datasets collection via the irds namespace
dataset = prepare_dataset("irds.msmarco-passage")

# Same API as native datasets
for doc in dataset.documents.iter_documents():
    print(doc)

The list below is auto-generated and may not reflect the exact version of ir-datasets installed on your system.

Data Types

These wrapper types provide the datamaestro interface for ir-datasets data:

XPM Configdatamaestro_text.datasets.irds.data.Topics(*, irds, id)

Bases: TopicsStore, IRDSId

irds: str

The id to load the dataset from ir_datasets

id: str

The unique (sub-)dataset ID

XPM Configdatamaestro_text.datasets.irds.data.Documents(*, irds, id, count, file_access)

Bases: DocumentStore, IRDSId

irds: str

The id to load the dataset from ir_datasets

id: str

The unique (sub-)dataset ID

count: int

Number of documents

file_access: FileAccess = FileAccess.MMAP

How to access the file collection (might not have any impact, depends on the docstore)

XPM Configdatamaestro_text.datasets.irds.data.AdhocAssessments(*, irds, id)

Bases: AdhocAssessments, IRDSId

irds: str

The id to load the dataset from ir_datasets

id: str

The unique (sub-)dataset ID

See also LZ4DocumentStore in the Information Retrieval API section.

Available Datasets

ANTIQUE

<p> “ANTIQUE is a non-factoid quesiton answering dataset based on the questions and answers of Yahoo! Webscope L6.” </p> <ul> <li>Documents: Short answer passages (from Yahoo Answers)</li> <li>Queries: Natural language questions (from Yahoo Answers)</li> <li><a href=”https://arxiv.org/abs/1905.08957”>Dataset Paper</a></li> </ul>

Dataset irds.antique.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> “ANTIQUE is a non-factoid quesiton answering dataset based on the questions and answers of Yahoo! Webscope L6.” </p> <ul> <li>Documents: Short answer passages (from Yahoo Answers)</li> <li>Queries: Natural language questions (from Yahoo Answers)</li> <li><a href=”https://arxiv.org/abs/1905.08957”>Dataset Paper</a></li> </ul>

Dataset irds.antique.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test set of the ANTIQUE dataset. </p>

Dataset irds.antique.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test set of the ANTIQUE dataset. </p>

Dataset irds.antique.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test set of the ANTIQUE dataset. </p>

Dataset irds.antique.test.non-offensive.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>antique/test</a> without a set of queries deemed by the authors of ANTIQUE to be “offensive (and noisy).” </p>

Dataset irds.antique.test.non-offensive.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>antique/test</a> without a set of queries deemed by the authors of ANTIQUE to be “offensive (and noisy).” </p>

Dataset irds.antique.test.non-offensive

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>antique/test</a> without a set of queries deemed by the authors of ANTIQUE to be “offensive (and noisy).” </p>

Dataset irds.antique.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set of the ANTIQUE dataset. </p>

Dataset irds.antique.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set of the ANTIQUE dataset. </p>

Dataset irds.antique.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set of the ANTIQUE dataset. </p>

Dataset irds.antique.train.split200-train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>antique/train</a> without the 200 queries used by <a class=”ds-ref”>antique/train/split200-valid</a>. </p>

Dataset irds.antique.train.split200-train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>antique/train</a> without the 200 queries used by <a class=”ds-ref”>antique/train/split200-valid</a>. </p>

Dataset irds.antique.train.split200-train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>antique/train</a> without the 200 queries used by <a class=”ds-ref”>antique/train/split200-valid</a>. </p>

Dataset irds.antique.train.split200-valid.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A held-out subset of 200 queries from <a class=”ds-ref”>antique/train</a>. Use in conjunction with <a class=”ds-ref”>antique/train/split200-train</a>. </p>

Dataset irds.antique.train.split200-valid.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A held-out subset of 200 queries from <a class=”ds-ref”>antique/train</a>. Use in conjunction with <a class=”ds-ref”>antique/train/split200-train</a>. </p>

Dataset irds.antique.train.split200-valid

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A held-out subset of 200 queries from <a class=”ds-ref”>antique/train</a>. Use in conjunction with <a class=”ds-ref”>antique/train/split200-train</a>. </p>

AOL-IA (Internet Archive)

<p> This is a version of the AOL Query Log. Documents use versions that appeared around the time of the query log (early 2006) via the Internet Archive. </p> <p> The query log does not include document or query IDs. These are instead created by ir_datasets. Document IDs are assigned using a hash of the URL that appears in the query log. Query IDs are assigned using the a hash of the noramlised query. All unique normalized queries are available from <kbd>queries</kbd>, and all clicked documents are available from <kbd>qrels</kbd> (iteration value set to the user ID). Full information (including original query) are available from <kbd>qlogs</kbd>. </p>

Dataset irds.aol-ia.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> This is a version of the AOL Query Log. Documents use versions that appeared around the time of the query log (early 2006) via the Internet Archive. </p> <p> The query log does not include document or query IDs. These are instead created by ir_datasets. Document IDs are assigned using a hash of the URL that appears in the query log. Query IDs are assigned using the a hash of the noramlised query. All unique normalized queries are available from <kbd>queries</kbd>, and all clicked documents are available from <kbd>qrels</kbd> (iteration value set to the user ID). Full information (including original query) are available from <kbd>qlogs</kbd>. </p>

Dataset irds.aol-ia.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> This is a version of the AOL Query Log. Documents use versions that appeared around the time of the query log (early 2006) via the Internet Archive. </p> <p> The query log does not include document or query IDs. These are instead created by ir_datasets. Document IDs are assigned using a hash of the URL that appears in the query log. Query IDs are assigned using the a hash of the noramlised query. All unique normalized queries are available from <kbd>queries</kbd>, and all clicked documents are available from <kbd>qrels</kbd> (iteration value set to the user ID). Full information (including original query) are available from <kbd>qlogs</kbd>. </p>

Dataset irds.aol-ia.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> This is a version of the AOL Query Log. Documents use versions that appeared around the time of the query log (early 2006) via the Internet Archive. </p> <p> The query log does not include document or query IDs. These are instead created by ir_datasets. Document IDs are assigned using a hash of the URL that appears in the query log. Query IDs are assigned using the a hash of the noramlised query. All unique normalized queries are available from <kbd>queries</kbd>, and all clicked documents are available from <kbd>qrels</kbd> (iteration value set to the user ID). Full information (including original query) are available from <kbd>qlogs</kbd>. </p>

Dataset irds.aol-ia

→ datamaestro_text.datasets.irds.data.Adhoc

<p> This is a version of the AOL Query Log. Documents use versions that appeared around the time of the query log (early 2006) via the Internet Archive. </p> <p> The query log does not include document or query IDs. These are instead created by ir_datasets. Document IDs are assigned using a hash of the URL that appears in the query log. Query IDs are assigned using the a hash of the noramlised query. All unique normalized queries are available from <kbd>queries</kbd>, and all clicked documents are available from <kbd>qrels</kbd> (iteration value set to the user ID). Full information (including original query) are available from <kbd>qlogs</kbd>. </p>

AQUAINT

<p> A document collection of about 1M English newswire text. Sources are the Xinhua News Service (People’s Republic of China), the New York Times News Service, and the Associated Press Worldstream News Service. </p> <ul> <li><a href=”https://catalog.ldc.upenn.edu/LDC2002T31”>Dataset details</a></li> </ul>

Dataset irds.aquaint.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A document collection of about 1M English newswire text. Sources are the Xinhua News Service (People’s Republic of China), the New York Times News Service, and the Associated Press Worldstream News Service. </p> <ul> <li><a href=”https://catalog.ldc.upenn.edu/LDC2002T31”>Dataset details</a></li> </ul>

Dataset irds.aquaint.trec-robust-2005.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Robust 2005 dataset. Contains a subset of 50 “hard” queries from <a class=”ds-ref”>trec-robust04</a>. </p> <ul> <li>Documents: News articles</li> <li>Queries: keyword queries, descriptions, narratives</li> <li>Relevance: Deep judgments</li> <li><a href=”https://trec.nist.gov/data/robust/05/05.guidelines.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/ROBUST.OVERVIEW.pdf”>Task overview paper</a></li> <li>See also: <a class=”ds-ref”>trec-robust04</a></li> </ul>

Dataset irds.aquaint.trec-robust-2005.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Robust 2005 dataset. Contains a subset of 50 “hard” queries from <a class=”ds-ref”>trec-robust04</a>. </p> <ul> <li>Documents: News articles</li> <li>Queries: keyword queries, descriptions, narratives</li> <li>Relevance: Deep judgments</li> <li><a href=”https://trec.nist.gov/data/robust/05/05.guidelines.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/ROBUST.OVERVIEW.pdf”>Task overview paper</a></li> <li>See also: <a class=”ds-ref”>trec-robust04</a></li> </ul>

Dataset irds.aquaint.trec-robust-2005

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Robust 2005 dataset. Contains a subset of 50 “hard” queries from <a class=”ds-ref”>trec-robust04</a>. </p> <ul> <li>Documents: News articles</li> <li>Queries: keyword queries, descriptions, narratives</li> <li>Relevance: Deep judgments</li> <li><a href=”https://trec.nist.gov/data/robust/05/05.guidelines.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/ROBUST.OVERVIEW.pdf”>Task overview paper</a></li> <li>See also: <a class=”ds-ref”>trec-robust04</a></li> </ul>

args.me version 1.0

<p> Corpus version 1.0 with 387 606 arguments crawled from Debatewise, IDebate.org, Debatepedia, Debate.org. It was released on July 9, 2019 on <a href=”https://zenodo.org/record/3274636”>Zenodo</a>. The cleaned version <a class=”ds-ref”>argsme/1.0-cleaned</a> should be preferred. </p> <p> This collection is licensed with the <a href=”https://creativecommons.org/licenses/by/4.0/”>Creative Commons Attribution 4.0 International</a>. Individual rights to the content still apply. </p>

Dataset irds.argsme.1.0.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Corpus version 1.0 with 387 606 arguments crawled from Debatewise, IDebate.org, Debatepedia, Debate.org. It was released on July 9, 2019 on <a href=”https://zenodo.org/record/3274636”>Zenodo</a>. The cleaned version <a class=”ds-ref”>argsme/1.0-cleaned</a> should be preferred. </p> <p> This collection is licensed with the <a href=”https://creativecommons.org/licenses/by/4.0/”>Creative Commons Attribution 4.0 International</a>. Individual rights to the content still apply. </p>

Dataset irds.argsme.1.0.touche-2020-task-1.uncorrected.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>argsme/2020-04-01/touche-2020-task-1</a> that uses the <a class=”ds-ref”>argsme/1.0</a> corpus with uncorrected relevance judgements derived from crowdworkers. This dataset’s relevance judgements should <em>not</em> be used without preprocessing. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.argsme.1.0.touche-2020-task-1.uncorrected.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>argsme/2020-04-01/touche-2020-task-1</a> that uses the <a class=”ds-ref”>argsme/1.0</a> corpus with uncorrected relevance judgements derived from crowdworkers. This dataset’s relevance judgements should <em>not</em> be used without preprocessing. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.argsme.1.0.touche-2020-task-1.uncorrected

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>argsme/2020-04-01/touche-2020-task-1</a> that uses the <a class=”ds-ref”>argsme/1.0</a> corpus with uncorrected relevance judgements derived from crowdworkers. This dataset’s relevance judgements should <em>not</em> be used without preprocessing. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

args.me version 1.0 cleaned

<p> Corpus version 1.0-cleaned with 382 545 arguments crawled from Debatewise, IDebate.org, Debatepedia, Debate.org. This version contains the same arguments as <a class=”ds-ref”>argsme/1.0</a>, but was cleaned as described in the corresponding publication. It was released on October 27, 2020 on <a href=”https://zenodo.org/record/4139439”>Zenodo</a>. </p> <p> This collection is licensed with the <a href=”https://creativecommons.org/licenses/by/4.0/”>Creative Commons Attribution 4.0 International</a>. Individual rights to the content still apply. </p>

Dataset irds.argsme.1.0-cleaned.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Corpus version 1.0-cleaned with 382 545 arguments crawled from Debatewise, IDebate.org, Debatepedia, Debate.org. This version contains the same arguments as <a class=”ds-ref”>argsme/1.0</a>, but was cleaned as described in the corresponding publication. It was released on October 27, 2020 on <a href=”https://zenodo.org/record/4139439”>Zenodo</a>. </p> <p> This collection is licensed with the <a href=”https://creativecommons.org/licenses/by/4.0/”>Creative Commons Attribution 4.0 International</a>. Individual rights to the content still apply. </p>

argsme/2020-04-01/debateorg

<p> Subset of the 338 620 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from the debate portal Debate.org. </p>

Dataset irds.argsme.2020-04-01.debateorg.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of the 338 620 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from the debate portal Debate.org. </p>

argsme/2020-04-01/debatepedia

<p> Subset of the 21 197 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from the debate portal Debatepedia. </p>

Dataset irds.argsme.2020-04-01.debatepedia.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of the 21 197 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from the debate portal Debatepedia. </p>

argsme/2020-04-01/debatewise

<p> Subset of the 14 353 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from the debate portal Debatewise. </p>

Dataset irds.argsme.2020-04-01.debatewise.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of the 14 353 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from the debate portal Debatewise. </p>

argsme/2020-04-01/idebate

<p> Subset of the 13 522 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from the debate portal IDebate.org. </p>

Dataset irds.argsme.2020-04-01.idebate.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of the 13 522 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from the debate portal IDebate.org. </p>

argsme/2020-04-01/parliamentary

<p> Subset of the 48 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from Canadian Parliament discussions. </p>

Dataset irds.argsme.2020-04-01.parliamentary.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of the 48 arguments from <a class=”ds-ref”>argsme/2020-04-01</a> that were crawled from Canadian Parliament discussions. </p>

argsme/2020-04-01/processed

<p> Pre-processed version of <a class=”ds-ref”>argsme/2020-04-01</a> where each argument is split into sentences. </p>

Dataset irds.argsme.2020-04-01.processed.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Pre-processed version of <a class=”ds-ref”>argsme/2020-04-01</a> where each argument is split into sentences. </p>

Dataset irds.argsme.2020-04-01.processed.touche-2022-task-1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a query about a controversial topic, retrieve and rank a relevant pair of sentences from a collection of arguments (<a class=”ds-ref”>argsme/2020-04-01-processed</a>). </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/argument-retrieval-for-controversial-questions.html”>Task 1 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.argsme.2020-04-01.processed.touche-2022-task-1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a query about a controversial topic, retrieve and rank a relevant pair of sentences from a collection of arguments (<a class=”ds-ref”>argsme/2020-04-01-processed</a>). </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/argument-retrieval-for-controversial-questions.html”>Task 1 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.argsme.2020-04-01.processed.touche-2022-task-1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a query about a controversial topic, retrieve and rank a relevant pair of sentences from a collection of arguments (<a class=”ds-ref”>argsme/2020-04-01-processed</a>). </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/argument-retrieval-for-controversial-questions.html”>Task 1 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

args.me

<p> Corpus version 2020-04-01 with 387 740 arguments crawled from Debatewise, IDebate.org, Debatepedia, Debate.org, and from Canadian Parliament discussions. It was released on April 1, 2020 on <a href=”https://zenodo.org/record/3734893”>Zenodo</a>. </p> <p> This collection is licensed with the <a href=”https://creativecommons.org/licenses/by/4.0/”>Creative Commons Attribution 4.0 International</a>. Individual rights to the content still apply. </p>

Dataset irds.argsme.2020-04-01.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Corpus version 2020-04-01 with 387 740 arguments crawled from Debatewise, IDebate.org, Debatepedia, Debate.org, and from Canadian Parliament discussions. It was released on April 1, 2020 on <a href=”https://zenodo.org/record/3734893”>Zenodo</a>. </p> <p> This collection is licensed with the <a href=”https://creativecommons.org/licenses/by/4.0/”>Creative Commons Attribution 4.0 International</a>. Individual rights to the content still apply. </p>

Dataset irds.argsme.2020-04-01.touche-2020-task-1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Decision making processes, be it at the societal or at the personal level, eventually come to a point where one side will challenge the other with a why-question, which is a prompt to justify one’s stance. Thus, technologies for argument mining and argumentation processing are maturing at a rapid pace, giving rise for the first time to argument retrieval. Touché 2020 is the first lab on Argument Retrieval at CLEF 2020 featuring two tasks. </p> <p> Given a question on a controversial topic, retrieve relevant arguments from a focused crawl of online debate portals (<a class=”ds-ref”>argsme/2020-04-01</a>). </p> <p> Documents are judged based on their general topical relevance. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.argsme.2020-04-01.touche-2020-task-1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Decision making processes, be it at the societal or at the personal level, eventually come to a point where one side will challenge the other with a why-question, which is a prompt to justify one’s stance. Thus, technologies for argument mining and argumentation processing are maturing at a rapid pace, giving rise for the first time to argument retrieval. Touché 2020 is the first lab on Argument Retrieval at CLEF 2020 featuring two tasks. </p> <p> Given a question on a controversial topic, retrieve relevant arguments from a focused crawl of online debate portals (<a class=”ds-ref”>argsme/2020-04-01</a>). </p> <p> Documents are judged based on their general topical relevance. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.argsme.2020-04-01.touche-2020-task-1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Decision making processes, be it at the societal or at the personal level, eventually come to a point where one side will challenge the other with a why-question, which is a prompt to justify one’s stance. Thus, technologies for argument mining and argumentation processing are maturing at a rapid pace, giving rise for the first time to argument retrieval. Touché 2020 is the first lab on Argument Retrieval at CLEF 2020 featuring two tasks. </p> <p> Given a question on a controversial topic, retrieve relevant arguments from a focused crawl of online debate portals (<a class=”ds-ref”>argsme/2020-04-01</a>). </p> <p> Documents are judged based on their general topical relevance. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.argsme.2020-04-01.touche-2021-task-1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2021 is the second lab on argument retrieval at CLEF 2021 featuring two tasks. </p> <p> Given a question on a controversial topic, retrieve relevant arguments from a focused crawl of online debate portals (<a class=”ds-ref”>argsme/2020-04-01</a>). </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://webis.de/events/touche-21/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-21/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-85251-1_28”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI8FDfYnzcjbsf26RIatNgM3”>Workshop videos</a></li> </ul>

Dataset irds.argsme.2020-04-01.touche-2021-task-1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2021 is the second lab on argument retrieval at CLEF 2021 featuring two tasks. </p> <p> Given a question on a controversial topic, retrieve relevant arguments from a focused crawl of online debate portals (<a class=”ds-ref”>argsme/2020-04-01</a>). </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://webis.de/events/touche-21/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-21/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-85251-1_28”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI8FDfYnzcjbsf26RIatNgM3”>Workshop videos</a></li> </ul>

Dataset irds.argsme.2020-04-01.touche-2021-task-1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2021 is the second lab on argument retrieval at CLEF 2021 featuring two tasks. </p> <p> Given a question on a controversial topic, retrieve relevant arguments from a focused crawl of online debate portals (<a class=”ds-ref”>argsme/2020-04-01</a>). </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://webis.de/events/touche-21/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-21/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-85251-1_28”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI8FDfYnzcjbsf26RIatNgM3”>Workshop videos</a></li> </ul>

Dataset irds.argsme.2020-04-01.touche-2020-task-1.uncorrected.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>argsme/2020-04-01/touche-2020-task-1</a> that uses uncorrected relevance judgements derived from crowdworkers. This dataset’s relevance judgements should <em>not</em> be used without preprocessing. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.argsme.2020-04-01.touche-2020-task-1.uncorrected.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>argsme/2020-04-01/touche-2020-task-1</a> that uses uncorrected relevance judgements derived from crowdworkers. This dataset’s relevance judgements should <em>not</em> be used without preprocessing. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.argsme.2020-04-01.touche-2020-task-1.uncorrected

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>argsme/2020-04-01/touche-2020-task-1</a> that uses uncorrected relevance judgements derived from crowdworkers. This dataset’s relevance judgements should <em>not</em> be used without preprocessing. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-1.html”>Task 1 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

beir/arguana

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

Dataset irds.beir.arguana.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

Dataset irds.beir.arguana.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

Dataset irds.beir.arguana.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

Dataset irds.beir.arguana

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

beir/climate-fever

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

Dataset irds.beir.climate-fever.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

Dataset irds.beir.climate-fever.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

Dataset irds.beir.climate-fever.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

Dataset irds.beir.climate-fever

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

beir/cqadupstack/android

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>android</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.android.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>android</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.android.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>android</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.android.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>android</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.android

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>android</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/english

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>english</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.english.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>english</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.english.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>english</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.english.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>english</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.english

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>english</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/gaming

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gaming</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.gaming.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gaming</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.gaming.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gaming</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.gaming.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gaming</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.gaming

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gaming</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/gis

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gis</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.gis.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gis</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.gis.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gis</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.gis.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gis</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.gis

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>gis</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/mathematica

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>mathematica</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.mathematica.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>mathematica</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.mathematica.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>mathematica</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.mathematica.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>mathematica</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.mathematica

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>mathematica</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/physics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>physics</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.physics.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>physics</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.physics.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>physics</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.physics.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>physics</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.physics

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>physics</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/programmers

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>programmers</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.programmers.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>programmers</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.programmers.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>programmers</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.programmers.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>programmers</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.programmers

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>programmers</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/stats

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>stats</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.stats.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>stats</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.stats.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>stats</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.stats.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>stats</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.stats

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>stats</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/tex

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>tex</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.tex.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>tex</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.tex.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>tex</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.tex.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>tex</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.tex

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>tex</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/unix

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>unix</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.unix.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>unix</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.unix.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>unix</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.unix.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>unix</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.unix

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>unix</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/webmasters

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>webmasters</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.webmasters.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>webmasters</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.webmasters.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>webmasters</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.webmasters.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>webmasters</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.webmasters

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>webmasters</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/cqadupstack/wordpress

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>wordpress</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.wordpress.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>wordpress</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.wordpress.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>wordpress</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.wordpress.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>wordpress</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

Dataset irds.beir.cqadupstack.wordpress

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CQADupStack dataset, for duplicate question retrieval. This subset is from the <kbd>wordpress</kbd> StackExchange subforum. </p> <ul> <li><a href=”https://people.eng.unimelb.edu.au/tbaldwin/pubs/adcs2015.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cis.unimelb.edu.au/resources/cqadupstack/”>Dataset website</a></li> <li><a href=”https://github.com/D1Doris/CQADupStack”>Dataset repository</a></li> </ul>

beir/dbpedia-entity

<p> A version of the DBPedia-Entity-v2 dataset for entity retrieval. </p> <ul> <li><a href=”http://hasibi.com/files/sigir2017-dbpedia_entity.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/iai-group/DBpedia-Entity”>Dataset website</a></li> </ul>

Dataset irds.beir.dbpedia-entity.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the DBPedia-Entity-v2 dataset for entity retrieval. </p> <ul> <li><a href=”http://hasibi.com/files/sigir2017-dbpedia_entity.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/iai-group/DBpedia-Entity”>Dataset website</a></li> </ul>

Dataset irds.beir.dbpedia-entity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the DBPedia-Entity-v2 dataset for entity retrieval. </p> <ul> <li><a href=”http://hasibi.com/files/sigir2017-dbpedia_entity.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/iai-group/DBpedia-Entity”>Dataset website</a></li> </ul>

Dataset irds.beir.dbpedia-entity.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A random sample of 67 queries from the official test set, used as a dev set. </p>

Dataset irds.beir.dbpedia-entity.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A random sample of 67 queries from the official test set, used as a dev set. </p>

Dataset irds.beir.dbpedia-entity.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A random sample of 67 queries from the official test set, used as a dev set. </p>

Dataset irds.beir.dbpedia-entity.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A the official test set, without 67 queries used as a dev set. </p>

Dataset irds.beir.dbpedia-entity.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A the official test set, without 67 queries used as a dev set. </p>

Dataset irds.beir.dbpedia-entity.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A the official test set, without 67 queries used as a dev set. </p>

beir/fever

<p> A version of the FEVER dataset for fact verification. Includes queries from the /train /dev and /test subsets. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/N18-1074.pdf”>Dataset paper</a></li> <li><a href=”https://fever.ai/resources.html”>Dataset website</a></li> </ul>

Dataset irds.beir.fever.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the FEVER dataset for fact verification. Includes queries from the /train /dev and /test subsets. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/N18-1074.pdf”>Dataset paper</a></li> <li><a href=”https://fever.ai/resources.html”>Dataset website</a></li> </ul>

Dataset irds.beir.fever.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the FEVER dataset for fact verification. Includes queries from the /train /dev and /test subsets. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/N18-1074.pdf”>Dataset paper</a></li> <li><a href=”https://fever.ai/resources.html”>Dataset website</a></li> </ul>

Dataset irds.beir.fever.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The official dev set. </p>

Dataset irds.beir.fever.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The official dev set. </p>

Dataset irds.beir.fever.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The official dev set. </p>

Dataset irds.beir.fever.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The official test set. </p>

Dataset irds.beir.fever.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The official test set. </p>

Dataset irds.beir.fever.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The official test set. </p>

Dataset irds.beir.fever.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The official train set. </p>

Dataset irds.beir.fever.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The official train set. </p>

Dataset irds.beir.fever.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The official train set. </p>

beir/fiqa

<p> A version of the FIQA-2018 dataset (financial opinion question answering). Queries include those in the /train /dev and /test subsets. </p> <ul> <li><a href=”https://dl.acm.org/doi/10.1145/3184558.3192301”>Dataset paper</a></li> <li><a href=”https://sites.google.com/view/fiqa/home”>Dataset site</a></li> </ul>

Dataset irds.beir.fiqa.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the FIQA-2018 dataset (financial opinion question answering). Queries include those in the /train /dev and /test subsets. </p> <ul> <li><a href=”https://dl.acm.org/doi/10.1145/3184558.3192301”>Dataset paper</a></li> <li><a href=”https://sites.google.com/view/fiqa/home”>Dataset site</a></li> </ul>

Dataset irds.beir.fiqa.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the FIQA-2018 dataset (financial opinion question answering). Queries include those in the /train /dev and /test subsets. </p> <ul> <li><a href=”https://dl.acm.org/doi/10.1145/3184558.3192301”>Dataset paper</a></li> <li><a href=”https://sites.google.com/view/fiqa/home”>Dataset site</a></li> </ul>

Dataset irds.beir.fiqa.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Random sample of 500 queries from the official dataset. </p>

Dataset irds.beir.fiqa.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Random sample of 500 queries from the official dataset. </p>

Dataset irds.beir.fiqa.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Random sample of 500 queries from the official dataset. </p>

Dataset irds.beir.fiqa.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Random sample of 648 queries from the official dataset. </p>

Dataset irds.beir.fiqa.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Random sample of 648 queries from the official dataset. </p>

Dataset irds.beir.fiqa.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Random sample of 648 queries from the official dataset. </p>

Dataset irds.beir.fiqa.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dataset without the 1148 queries sampled for /dev and /test. </p>

Dataset irds.beir.fiqa.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dataset without the 1148 queries sampled for /dev and /test. </p>

Dataset irds.beir.fiqa.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dataset without the 1148 queries sampled for /dev and /test. </p>

beir/hotpotqa

<p> A version of the Hotpot QA dataset for multi-hop question answering. Queries include all those in /train /dev and /test. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/D18-1259”>Dataset paper</a></li> <li><a href=”https://github.com/hotpotqa/hotpot”>Dataset website</a></li> </ul>

Dataset irds.beir.hotpotqa.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the Hotpot QA dataset for multi-hop question answering. Queries include all those in /train /dev and /test. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/D18-1259”>Dataset paper</a></li> <li><a href=”https://github.com/hotpotqa/hotpot”>Dataset website</a></li> </ul>

Dataset irds.beir.hotpotqa.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the Hotpot QA dataset for multi-hop question answering. Queries include all those in /train /dev and /test. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/D18-1259”>Dataset paper</a></li> <li><a href=”https://github.com/hotpotqa/hotpot”>Dataset website</a></li> </ul>

Dataset irds.beir.hotpotqa.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Random selection of the 5447 queries from /train. </p>

Dataset irds.beir.hotpotqa.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Random selection of the 5447 queries from /train. </p>

Dataset irds.beir.hotpotqa.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Random selection of the 5447 queries from /train. </p>

Dataset irds.beir.hotpotqa.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official <em>dev</em> set from HotpotQA, here used as a test set. </p>

Dataset irds.beir.hotpotqa.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official <em>dev</em> set from HotpotQA, here used as a test set. </p>

Dataset irds.beir.hotpotqa.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official <em>dev</em> set from HotpotQA, here used as a test set. </p>

Dataset irds.beir.hotpotqa.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set, without the random selection of the 5447 queries used for /dev. </p>

Dataset irds.beir.hotpotqa.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set, without the random selection of the 5447 queries used for /dev. </p>

Dataset irds.beir.hotpotqa.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set, without the random selection of the 5447 queries used for /dev. </p>

beir/msmarco

<p> A version of the MS MARCO passage ranking dataset. Includes queries from the /train, /dev, and /test sub-datasets. </p> <p> Note that this version differs from <a class=”ds-ref”>msmarco-passage</a>, in that it does not correct the encoding problems in the source documents. </p> <ul> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> </ul>

Dataset irds.beir.msmarco.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the MS MARCO passage ranking dataset. Includes queries from the /train, /dev, and /test sub-datasets. </p> <p> Note that this version differs from <a class=”ds-ref”>msmarco-passage</a>, in that it does not correct the encoding problems in the source documents. </p> <ul> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> </ul>

Dataset irds.beir.msmarco.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the MS MARCO passage ranking dataset. Includes queries from the /train, /dev, and /test sub-datasets. </p> <p> Note that this version differs from <a class=”ds-ref”>msmarco-passage</a>, in that it does not correct the encoding problems in the source documents. </p> <ul> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> </ul>

Dataset irds.beir.msmarco.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the MS MARCO passage ranking dev set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/dev</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.beir.msmarco.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the MS MARCO passage ranking dev set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/dev</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.beir.msmarco.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the MS MARCO passage ranking dev set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/dev</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.beir.msmarco.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the TREC Deep Learning 2019 set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a></li> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.beir.msmarco.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the TREC Deep Learning 2019 set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a></li> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.beir.msmarco.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the TREC Deep Learning 2019 set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a></li> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.beir.msmarco.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the MS MARCO passage ranking train set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/train</a></li> </ul>

Dataset irds.beir.msmarco.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the MS MARCO passage ranking train set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/train</a></li> </ul>

Dataset irds.beir.msmarco.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the MS MARCO passage ranking train set. </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage/train</a></li> </ul>

beir/nfcorpus

<p> A version of the NF Corpus (Nutrition Facts). Queries use the “title” variant of the query, which here are often natural language questions. Queries include all those from /train /dev and /test. </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>nfcorpus</a>. </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> <li>See also: <a class=”ds-ref”>nfcorpus</a></li> </ul>

Dataset irds.beir.nfcorpus.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the NF Corpus (Nutrition Facts). Queries use the “title” variant of the query, which here are often natural language questions. Queries include all those from /train /dev and /test. </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>nfcorpus</a>. </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> <li>See also: <a class=”ds-ref”>nfcorpus</a></li> </ul>

Dataset irds.beir.nfcorpus.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the NF Corpus (Nutrition Facts). Queries use the “title” variant of the query, which here are often natural language questions. Queries include all those from /train /dev and /test. </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>nfcorpus</a>. </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> <li>See also: <a class=”ds-ref”>nfcorpus</a></li> </ul>

Dataset irds.beir.nfcorpus.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Combined dev set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/dev</a></li> </ul>

Dataset irds.beir.nfcorpus.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Combined dev set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/dev</a></li> </ul>

Dataset irds.beir.nfcorpus.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Combined dev set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/dev</a></li> </ul>

Dataset irds.beir.nfcorpus.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Combined test set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/test</a></li> </ul>

Dataset irds.beir.nfcorpus.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Combined test set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/test</a></li> </ul>

Dataset irds.beir.nfcorpus.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Combined test set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/test</a></li> </ul>

Dataset irds.beir.nfcorpus.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Combined train set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/train</a></li> </ul>

Dataset irds.beir.nfcorpus.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Combined train set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/train</a></li> </ul>

Dataset irds.beir.nfcorpus.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Combined train set of NFCorpus. </p> <ul> <li>See also: <a class=”ds-ref”>nfcorpus/train</a></li> </ul>

beir/nq

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

Dataset irds.beir.nq.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

Dataset irds.beir.nq.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

Dataset irds.beir.nq.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

Dataset irds.beir.nq

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

beir/quora

<p> A version of the Quora duplicate question detection dataset (QQP). Includes queries from /dev and /test sets. </p> <ul> <li><a href=”https://www.kaggle.com/c/quora-question-pairs”>Dataset website</a></li> </ul>

Dataset irds.beir.quora.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the Quora duplicate question detection dataset (QQP). Includes queries from /dev and /test sets. </p> <ul> <li><a href=”https://www.kaggle.com/c/quora-question-pairs”>Dataset website</a></li> </ul>

Dataset irds.beir.quora.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the Quora duplicate question detection dataset (QQP). Includes queries from /dev and /test sets. </p> <ul> <li><a href=”https://www.kaggle.com/c/quora-question-pairs”>Dataset website</a></li> </ul>

Dataset irds.beir.quora.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A 5,000 question subset of the original dataset, without overlaps in the other subsets. </p>

Dataset irds.beir.quora.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A 5,000 question subset of the original dataset, without overlaps in the other subsets. </p>

Dataset irds.beir.quora.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A 5,000 question subset of the original dataset, without overlaps in the other subsets. </p>

Dataset irds.beir.quora.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A 10,000 question subset of the original dataset, without overlaps in the other subsets. </p>

Dataset irds.beir.quora.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A 10,000 question subset of the original dataset, without overlaps in the other subsets. </p>

Dataset irds.beir.quora.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A 10,000 question subset of the original dataset, without overlaps in the other subsets. </p>

beir/scidocs

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

Dataset irds.beir.scidocs.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

Dataset irds.beir.scidocs.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

Dataset irds.beir.scidocs.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

Dataset irds.beir.scidocs

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

beir/scifact

<p> A version of the SciFact dataset, for fact verification. Queries include those form the /train and /test sets. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset paper</a></li> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset website</a></li> </ul>

Dataset irds.beir.scifact.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the SciFact dataset, for fact verification. Queries include those form the /train and /test sets. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset paper</a></li> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset website</a></li> </ul>

Dataset irds.beir.scifact.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the SciFact dataset, for fact verification. Queries include those form the /train and /test sets. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset paper</a></li> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset website</a></li> </ul>

Dataset irds.beir.scifact.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The official <em>dev</em> set. </p>

Dataset irds.beir.scifact.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The official <em>dev</em> set. </p>

Dataset irds.beir.scifact.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The official <em>dev</em> set. </p>

Dataset irds.beir.scifact.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The official train set. </p>

Dataset irds.beir.scifact.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The official train set. </p>

Dataset irds.beir.scifact.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The official train set. </p>

beir/trec-covid

<p> A version of the TREC COVID (complete) dataset, with titles and abstracts as documents. Queries are the question variant. </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>cord19/trec-covid</a>. </p> <ul> <li><a href=”https://www.semanticscholar.org/cord19”>Document collection site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>cord19/trec-covid</a></li> </ul>

Dataset irds.beir.trec-covid.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the TREC COVID (complete) dataset, with titles and abstracts as documents. Queries are the question variant. </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>cord19/trec-covid</a>. </p> <ul> <li><a href=”https://www.semanticscholar.org/cord19”>Document collection site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>cord19/trec-covid</a></li> </ul>

Dataset irds.beir.trec-covid.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the TREC COVID (complete) dataset, with titles and abstracts as documents. Queries are the question variant. </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>cord19/trec-covid</a>. </p> <ul> <li><a href=”https://www.semanticscholar.org/cord19”>Document collection site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>cord19/trec-covid</a></li> </ul>

Dataset irds.beir.trec-covid.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the TREC COVID (complete) dataset, with titles and abstracts as documents. Queries are the question variant. </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>cord19/trec-covid</a>. </p> <ul> <li><a href=”https://www.semanticscholar.org/cord19”>Document collection site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>cord19/trec-covid</a></li> </ul>

Dataset irds.beir.trec-covid

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the TREC COVID (complete) dataset, with titles and abstracts as documents. Queries are the question variant. </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>cord19/trec-covid</a>. </p> <ul> <li><a href=”https://www.semanticscholar.org/cord19”>Document collection site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>cord19/trec-covid</a></li> </ul>

beir/webis-touche2020

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.beir.webis-touche2020.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.beir.webis-touche2020.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.beir.webis-touche2020.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.beir.webis-touche2020

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

beir/webis-touche2020/v2

<p> Version 2 of the Touchè-2020 dataset, for argument retrieval. This version uses the “corrected” version of the qrels, mapped to version 1 of the corpus. </p> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.beir.webis-touche2020.v2.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version 2 of the Touchè-2020 dataset, for argument retrieval. This version uses the “corrected” version of the qrels, mapped to version 1 of the corpus. </p> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.beir.webis-touche2020.v2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version 2 of the Touchè-2020 dataset, for argument retrieval. This version uses the “corrected” version of the qrels, mapped to version 1 of the corpus. </p> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.beir.webis-touche2020.v2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version 2 of the Touchè-2020 dataset, for argument retrieval. This version uses the “corrected” version of the qrels, mapped to version 1 of the corpus. </p> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.beir.webis-touche2020.v2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version 2 of the Touchè-2020 dataset, for argument retrieval. This version uses the “corrected” version of the qrels, mapped to version 1 of the corpus. </p> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

c4/en-noclean-tr

<p> The “en-noclean” train subset of the corpus, consisting of ~1B documents written in English. Document IDs are assigned as proposed by the <a href=”https://trec-health-misinfo.github.io/”> TREC Health Misinformation 2021 track</a>. </p>

Dataset irds.c4.en-noclean-tr.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The “en-noclean” train subset of the corpus, consisting of ~1B documents written in English. Document IDs are assigned as proposed by the <a href=”https://trec-health-misinfo.github.io/”> TREC Health Misinformation 2021 track</a>. </p>

Dataset irds.c4.en-noclean-tr.trec-misinfo-2021.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Health Misinformation 2021 track. </p> <ul> <li><a href=”https://trec-health-misinfo.github.io/”>Shared Task Website</a> </ul>

car/v1.5

<p> Version 1.5 of the TREC dataset. This version is used for year 1 (2017) of the TREC CAR shared task. </p>

Dataset irds.car.v1.5.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version 1.5 of the TREC dataset. This version is used for year 1 (2017) of the TREC CAR shared task. </p>

Dataset irds.car.v1.5.test200.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Un-official test set consisting of manually-selected articles. Sometimes used as a validation set. </p>

Dataset irds.car.v1.5.test200.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Un-official test set consisting of manually-selected articles. Sometimes used as a validation set. </p>

Dataset irds.car.v1.5.test200

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Un-official test set consisting of manually-selected articles. Sometimes used as a validation set. </p>

Dataset irds.car.v1.5.train.fold0.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 0 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold0.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 0 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold0

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 0 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 1 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 1 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 1 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 2 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 2 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 2 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 3 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 3 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold3

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 3 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold4.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 4 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold4.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 4 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.train.fold4

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 4 of the official large training set for TREC CAR 2017. Relevance assumed from hierarchical structure of pages (i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.trec-y1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test set of TREC CAR 2017 (year 1). </p>

Dataset irds.car.v1.5.trec-y1.auto.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test set of TREC CAR 2017 (year 1), using automatic relevance judgments (assumed from hierarchical structure of pages, i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.trec-y1.auto.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test set of TREC CAR 2017 (year 1), using automatic relevance judgments (assumed from hierarchical structure of pages, i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.trec-y1.auto

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test set of TREC CAR 2017 (year 1), using automatic relevance judgments (assumed from hierarchical structure of pages, i.e., paragraphs under a header are assumed relevant.) </p>

Dataset irds.car.v1.5.trec-y1.manual.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test set of TREC CAR 2017 (year 1), using manual graded relevance judgments. </p>

Dataset irds.car.v1.5.trec-y1.manual.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test set of TREC CAR 2017 (year 1), using manual graded relevance judgments. </p>

Dataset irds.car.v1.5.trec-y1.manual

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test set of TREC CAR 2017 (year 1), using manual graded relevance judgments. </p>

car/v2.0

<p> Version 2.0 of the TREC CAR dataset. </p>

Dataset irds.car.v2.0.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version 2.0 of the TREC CAR dataset. </p>

Highwire (TREC Genomics 2006-07)

<p> Medical document collection from <a href=”https://www.highwirepress.com/”>Highwire Press</a>. Includes 162,259 scientific articles from 49 journals. </p> <p> This dataset is used for the TREC 2006-07 TREC Genomics track. </p> <p> Note that these documents are split into passages based on paragraph tags in the HTML. </p> <ul> <li>Documents: Biomedical journal articles</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2006data.html#docs”>Information about document collection</a></li> </ul>

Dataset irds.highwire.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Medical document collection from <a href=”https://www.highwirepress.com/”>Highwire Press</a>. Includes 162,259 scientific articles from 49 journals. </p> <p> This dataset is used for the TREC 2006-07 TREC Genomics track. </p> <p> Note that these documents are split into passages based on paragraph tags in the HTML. </p> <ul> <li>Documents: Biomedical journal articles</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2006data.html#docs”>Information about document collection</a></li> </ul>

Dataset irds.highwire.trec-genomics-2006.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Genomics Track 2006 benchmark. Contains 28 queries with passage-level relevance judgments. </p> <ul> <li>Documents: Biomedical journal articles</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, by passage</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2006data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/GEO06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.highwire.trec-genomics-2006.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Genomics Track 2006 benchmark. Contains 28 queries with passage-level relevance judgments. </p> <ul> <li>Documents: Biomedical journal articles</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, by passage</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2006data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/GEO06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.highwire.trec-genomics-2006

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Genomics Track 2006 benchmark. Contains 28 queries with passage-level relevance judgments. </p> <ul> <li>Documents: Biomedical journal articles</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, by passage</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2006data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/GEO06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.highwire.trec-genomics-2007.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Genomics Track 2007 benchmark. Contains 36 queries with passage-level relevance judgments. </p> <ul> <li>Documents: Biomedical journal articles</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, by passage</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2007data.html”>Shared task data site</a></li> <li><a href=”https://dmice.ohsu.edu/hersh/trec-07-genomics.pdf”>Shared task paper</a></li> </ul>

Dataset irds.highwire.trec-genomics-2007.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Genomics Track 2007 benchmark. Contains 36 queries with passage-level relevance judgments. </p> <ul> <li>Documents: Biomedical journal articles</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, by passage</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2007data.html”>Shared task data site</a></li> <li><a href=”https://dmice.ohsu.edu/hersh/trec-07-genomics.pdf”>Shared task paper</a></li> </ul>

Dataset irds.highwire.trec-genomics-2007

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Genomics Track 2007 benchmark. Contains 36 queries with passage-level relevance judgments. </p> <ul> <li>Documents: Biomedical journal articles</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, by passage</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2007data.html”>Shared task data site</a></li> <li><a href=”https://dmice.ohsu.edu/hersh/trec-07-genomics.pdf”>Shared task paper</a></li> </ul>

medline/2004

<p> 3M Medline articles including titles and abstracts, used for the TREC 2004-05 Genomics track. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2004data.html”>Information about document collection</a></li> </ul>

Dataset irds.medline.2004.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> 3M Medline articles including titles and abstracts, used for the TREC 2004-05 Genomics track. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2004data.html”>Information about document collection</a></li> </ul>

Dataset irds.medline.2004.trec-genomics-2004.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Genomics Track 2004 benchmark. Contains 50 queries with article-level relevance judgments. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, graded</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2004data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/GEO.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2004.trec-genomics-2004.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Genomics Track 2004 benchmark. Contains 50 queries with article-level relevance judgments. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, graded</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2004data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/GEO.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2004.trec-genomics-2004

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Genomics Track 2004 benchmark. Contains 50 queries with article-level relevance judgments. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, graded</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2004data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/GEO.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2004.trec-genomics-2005.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Genomics Track 2005 benchmark. Contains 50 queries with article-level relevance judgments. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, graded</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2005data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/GEO.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2004.trec-genomics-2005.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Genomics Track 2005 benchmark. Contains 50 queries with article-level relevance judgments. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, graded</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2005data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/GEO.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2004.trec-genomics-2005

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Genomics Track 2005 benchmark. Contains 50 queries with article-level relevance judgments. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Natural language questions</li> <li>Qrels: deep, graded</li> <li><a href=”https://dmice.ohsu.edu/trec-gen/2005data.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/GEO.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

medline/2017

<p> 26M Medline and AACR/ASCO Proceedings articles including titles and abstracts. This collection is used for the TREC 2017-18 TREC Precision Medicine track. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li><a href=”http://www.trec-cds.org/2017.html”>Information about document collection</a></li> </ul>

Dataset irds.medline.2017.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> 26M Medline and AACR/ASCO Proceedings articles including titles and abstracts. This collection is used for the TREC 2017-18 TREC Precision Medicine track. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li><a href=”http://www.trec-cds.org/2017.html”>Information about document collection</a></li> </ul>

Dataset irds.medline.2017.trec-pm-2017.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Precision Medicine (PM) Track 2017 benchmark. Contains 30 queries containing disease, gene, and target demographic information. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Specific to TREC PM information need</li> <li>Qrels: deep, graded</li> <li><a href=”http://www.trec-cds.org/2017.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-PM.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2017.trec-pm-2017.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Precision Medicine (PM) Track 2017 benchmark. Contains 30 queries containing disease, gene, and target demographic information. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Specific to TREC PM information need</li> <li>Qrels: deep, graded</li> <li><a href=”http://www.trec-cds.org/2017.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-PM.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2017.trec-pm-2017

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Precision Medicine (PM) Track 2017 benchmark. Contains 30 queries containing disease, gene, and target demographic information. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Specific to TREC PM information need</li> <li>Qrels: deep, graded</li> <li><a href=”http://www.trec-cds.org/2017.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-PM.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2017.trec-pm-2018.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Precision Medicine (PM) Track 2018 benchmark. Contains 50 queries containing disease, gene, and target demographic information. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Specific to TREC PM information need</li> <li>Qrels: deep, graded</li> <li><a href=”http://www.trec-cds.org/2018.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-PM.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2017.trec-pm-2018.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Precision Medicine (PM) Track 2018 benchmark. Contains 50 queries containing disease, gene, and target demographic information. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Specific to TREC PM information need</li> <li>Qrels: deep, graded</li> <li><a href=”http://www.trec-cds.org/2018.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-PM.pdf”>Shared task paper</a></li> </ul>

Dataset irds.medline.2017.trec-pm-2018

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Precision Medicine (PM) Track 2018 benchmark. Contains 50 queries containing disease, gene, and target demographic information. </p> <ul> <li>Documents: Biomedical article titles and abstracts</li> <li>Queries: Specific to TREC PM information need</li> <li>Qrels: deep, graded</li> <li><a href=”http://www.trec-cds.org/2018.html”>Shared task data site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-PM.pdf”>Shared task paper</a></li> </ul>

clinicaltrials/2017

<p> A snapshot of <a href=”https://clinicaltrials.gov/”>ClinicalTrials.gov</a> from April 2017 for use with the <a class=”ds-ref”>clinicaltrials/2017/trec-pm-2017</a> and <a class=”ds-ref”>clinicaltrials/2017/trec-pm-2018</a> Clinical Trials subtasks. </p> <ul> <li><a href=”http://www.trec-cds.org/2017.html#documents”>Dataset information</a></li> </ul>

Dataset irds.clinicaltrials.2017.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A snapshot of <a href=”https://clinicaltrials.gov/”>ClinicalTrials.gov</a> from April 2017 for use with the <a class=”ds-ref”>clinicaltrials/2017/trec-pm-2017</a> and <a class=”ds-ref”>clinicaltrials/2017/trec-pm-2018</a> Clinical Trials subtasks. </p> <ul> <li><a href=”http://www.trec-cds.org/2017.html#documents”>Dataset information</a></li> </ul>

Dataset irds.clinicaltrials.2017.trec-pm-2017.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC 2017 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2017.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-PM.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>medline/2017/trec-pm-2017</a></li> </ul>

Dataset irds.clinicaltrials.2017.trec-pm-2017.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC 2017 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2017.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-PM.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>medline/2017/trec-pm-2017</a></li> </ul>

Dataset irds.clinicaltrials.2017.trec-pm-2017

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC 2017 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2017.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-PM.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>medline/2017/trec-pm-2017</a></li> </ul>

Dataset irds.clinicaltrials.2017.trec-pm-2018.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC 2018 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2018.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-PM.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>medline/2017/trec-pm-2018</a></li> </ul>

Dataset irds.clinicaltrials.2017.trec-pm-2018.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC 2018 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2018.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-PM.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>medline/2017/trec-pm-2018</a></li> </ul>

Dataset irds.clinicaltrials.2017.trec-pm-2018

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC 2018 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2018.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-PM.pdf”>Shared task paper</a></li> <li>See also: <a class=”ds-ref”>medline/2017/trec-pm-2018</a></li> </ul>

clinicaltrials/2019

<p> A snapshot of <a href=”https://clinicaltrials.gov/”>ClinicalTrials.gov</a> from May 2019 for use with the <a class=”ds-ref”>clinicaltrials/2019/trec-pm-2019</a> Clinical Trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2019.html#documents”>Dataset information</a></li> </ul>

Dataset irds.clinicaltrials.2019.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A snapshot of <a href=”https://clinicaltrials.gov/”>ClinicalTrials.gov</a> from May 2019 for use with the <a class=”ds-ref”>clinicaltrials/2019/trec-pm-2019</a> Clinical Trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2019.html#documents”>Dataset information</a></li> </ul>

Dataset irds.clinicaltrials.2019.trec-pm-2019.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC 2019 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2019.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.PM.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clinicaltrials.2019.trec-pm-2019.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC 2019 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2019.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.PM.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clinicaltrials.2019.trec-pm-2019

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC 2019 Precision Medicine clinical trials subtask. </p> <ul> <li><a href=”http://www.trec-cds.org/2019.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.PM.pdf”>Shared task paper</a></li> </ul>

clinicaltrials/2021

<p> A snapshot of <a href=”https://clinicaltrials.gov/”>ClinicalTrials.gov</a> from April 2021 for use with the <a href=”http://www.trec-cds.org/2021.html”>TREC Clinical Trials 2021 Track</a>. </p> <ul> <li><a href=”http://www.trec-cds.org/2021.html#documents”>Dataset information</a></li> </ul>

Dataset irds.clinicaltrials.2021.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A snapshot of <a href=”https://clinicaltrials.gov/”>ClinicalTrials.gov</a> from April 2021 for use with the <a href=”http://www.trec-cds.org/2021.html”>TREC Clinical Trials 2021 Track</a>. </p> <ul> <li><a href=”http://www.trec-cds.org/2021.html#documents”>Dataset information</a></li> </ul>

Dataset irds.clinicaltrials.2021.trec-ct-2021.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Clinical Trials 2021 track. </p> <ul> <li><a href=”http://www.trec-cds.org/2021.html”>Shared Task Website</a></li> </ul>

Dataset irds.clinicaltrials.2021.trec-ct-2021.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Clinical Trials 2021 track. </p> <ul> <li><a href=”http://www.trec-cds.org/2021.html”>Shared Task Website</a></li> </ul>

Dataset irds.clinicaltrials.2021.trec-ct-2021

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Clinical Trials 2021 track. </p> <ul> <li><a href=”http://www.trec-cds.org/2021.html”>Shared Task Website</a></li> </ul>

Dataset irds.clinicaltrials.2021.trec-ct-2022.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Clinical Trials 2022 track. </p> <ul> <li><a href=”https://www.trec-cds.org/2022.html”>Shared Task Website</a></li> </ul>

ClueWeb09

<p> ClueWeb 2009 web document collection. Contains over 1B web pages, in 10 languages. </p> <p> The dataset is obtained for a fee from CMU, and is shipped as hard drives. More information is provided <a href=”https://lemurproject.org/clueweb09/”>here</a>. </p> <ul> <li><a href=”https://lemurproject.org/clueweb09/”>Document collection site</a></li> </ul>

Dataset irds.clueweb09.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> ClueWeb 2009 web document collection. Contains over 1B web pages, in 10 languages. </p> <p> The dataset is obtained for a fee from CMU, and is shipped as hard drives. More information is provided <a href=”https://lemurproject.org/clueweb09/”>here</a>. </p> <ul> <li><a href=”https://lemurproject.org/clueweb09/”>Document collection site</a></li> </ul>

Dataset irds.clueweb09.trec-mq-2009.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> TREC 2009 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/MQ09OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.trec-mq-2009.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> TREC 2009 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/MQ09OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.trec-mq-2009

→ datamaestro_text.datasets.irds.data.Adhoc

<p> TREC 2009 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/MQ09OVERVIEW.pdf”>Shared task paper</a></li> </ul>

clueweb09/ar

<p> Subset of ClueWeb09 with only Arabic-language documents. </p>

Dataset irds.clueweb09.ar.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only Arabic-language documents. </p>

clueweb09/catb

<p> Subset of ClueWeb09 with the first ~50 million English-language documents. Used as a smaller collection for TREC Web Track tasks. </p>

Dataset irds.clueweb09.catb.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with the first ~50 million English-language documents. Used as a smaller collection for TREC Web Track tasks. </p>

Dataset irds.clueweb09.catb.trec-web-2009.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2009.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2009

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2009.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2009.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2009.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2010.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2010.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2010

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2010.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2010.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2010.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2011.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2011.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2011

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2011.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2011.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2011.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2012.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2012.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2012

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2012.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2012.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.catb.trec-web-2012.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

clueweb09/de

<p> Subset of ClueWeb09 with only German-language documents. </p>

Dataset irds.clueweb09.de.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only German-language documents. </p>

clueweb09/en

<p> Subset of ClueWeb09 with only English-language documents. </p>

Dataset irds.clueweb09.en.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only English-language documents. </p>

Dataset irds.clueweb09.en.trec-web-2009.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2009.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2009

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2009.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2009.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2009.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2009 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web09.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec18/papers/WEB09.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2010.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2010.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2010

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2010.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2010.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2010.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2010 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web10.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2011.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2011.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2011

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2011.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2011.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2011.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2011 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec20/papers/WEB.OVERVIEW.pdf”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2012.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2012.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2012

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2012.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2012.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb09.en.trec-web-2012.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2012 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2012.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec21/papers/WEB12.overview.pdf”>Shared task paper</a></li> </ul>

clueweb09/es

<p> Subset of ClueWeb09 with only Spanish-language documents. </p>

Dataset irds.clueweb09.es.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only Spanish-language documents. </p>

clueweb09/fr

<p> Subset of ClueWeb09 with only French-language documents. </p>

Dataset irds.clueweb09.fr.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only French-language documents. </p>

clueweb09/it

<p> Subset of ClueWeb09 with only Italian-language documents. </p>

Dataset irds.clueweb09.it.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only Italian-language documents. </p>

clueweb09/ja

<p> Subset of ClueWeb09 with only Japanese-language documents. </p>

Dataset irds.clueweb09.ja.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only Japanese-language documents. </p>

clueweb09/ko

<p> Subset of ClueWeb09 with only Korean-language documents. </p>

Dataset irds.clueweb09.ko.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only Korean-language documents. </p>

clueweb09/pt

<p> Subset of ClueWeb09 with only Portuguese-language documents. </p>

Dataset irds.clueweb09.pt.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only Portuguese-language documents. </p>

clueweb09/zh

<p> Subset of ClueWeb09 with only Chinese-language documents. </p>

Dataset irds.clueweb09.zh.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of ClueWeb09 with only Chinese-language documents. </p>

ClueWeb12

<p> ClueWeb 2012 web document collection. Contains 733M web pages. </p> <p> The dataset is obtained for a fee from CMU, and is shipped as hard drives. More information is provided <a href=”https://lemurproject.org/clueweb12/”>here</a>. </p> <ul> <li><a href=”https://lemurproject.org/clueweb12/”>Document collection site</a></li> <li><a href=”http://boston.lti.cs.cmu.edu/clueweb12/”>Dataset construction details</a></li> </ul>

Dataset irds.clueweb12.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> ClueWeb 2012 web document collection. Contains 733M web pages. </p> <p> The dataset is obtained for a fee from CMU, and is shipped as hard drives. More information is provided <a href=”https://lemurproject.org/clueweb12/”>here</a>. </p> <ul> <li><a href=”https://lemurproject.org/clueweb12/”>Document collection site</a></li> <li><a href=”http://boston.lti.cs.cmu.edu/clueweb12/”>Dataset construction details</a></li> </ul>

Dataset irds.clueweb12.trec-web-2013.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2013 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2013.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2013.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2013 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2013.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2013

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2013 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2013.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2013.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2013 diverse ranking benchmark. Contains 50 queries with deep subtopic relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2013.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2013.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2013 diverse ranking benchmark. Contains 50 queries with deep subtopic relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2013.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2013.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2013 diverse ranking benchmark. Contains 50 queries with deep subtopic relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2013.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2014.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2014 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2014.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2014.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2014 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2014.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2014

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2014 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2014.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2014.diversity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2014 diverse ranking benchmark. Contains 50 queries with deep subtopic relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2014.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2014.diversity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2014 diverse ranking benchmark. Contains 50 queries with deep subtopic relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2014.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.trec-web-2014.diversity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2014 diverse ranking benchmark. Contains 50 queries with deep subtopic relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/web2014.html”>Shared task site</a></li> <li><a href=”http://www-personal.umich.edu/~kevynct/pubs/trec-web-2014-overview.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.touche-2020-task-2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Decision making processes, be it at the societal or at the personal level, eventually come to a point where one side will challenge the other with a why-question, which is a prompt to justify one’s stance. Thus, technologies for argument mining and argumentation processing are maturing at a rapid pace, giving rise for the first time to argument retrieval. Touché 2020 is the first lab on Argument Retrieval at CLEF 2020 featuring two tasks. </p> <p> Given a comparative question, retrieve and rank documents from the ClueWeb12 that help to answer the comparative question. </p> <p> Documents are judged based on their general topical relevance. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-2.html”>Task 2 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.clueweb12.touche-2020-task-2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Decision making processes, be it at the societal or at the personal level, eventually come to a point where one side will challenge the other with a why-question, which is a prompt to justify one’s stance. Thus, technologies for argument mining and argumentation processing are maturing at a rapid pace, giving rise for the first time to argument retrieval. Touché 2020 is the first lab on Argument Retrieval at CLEF 2020 featuring two tasks. </p> <p> Given a comparative question, retrieve and rank documents from the ClueWeb12 that help to answer the comparative question. </p> <p> Documents are judged based on their general topical relevance. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-2.html”>Task 2 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.clueweb12.touche-2020-task-2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Decision making processes, be it at the societal or at the personal level, eventually come to a point where one side will challenge the other with a why-question, which is a prompt to justify one’s stance. Thus, technologies for argument mining and argumentation processing are maturing at a rapid pace, giving rise for the first time to argument retrieval. Touché 2020 is the first lab on Argument Retrieval at CLEF 2020 featuring two tasks. </p> <p> Given a comparative question, retrieve and rank documents from the ClueWeb12 that help to answer the comparative question. </p> <p> Documents are judged based on their general topical relevance. </p> <ul> <li><a href=”https://webis.de/events/touche-20/shared-task-2.html”>Task 2 website</a></li> <li><a href=”https://webis.de/events/touche-20/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-58219-7_26”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI90NnCLg9f4g32KLuOfPXR4”>Workshop videos</a></li> </ul>

Dataset irds.clueweb12.touche-2021-task-2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2021 is the second lab on argument retrieval at CLEF 2021 featuring two tasks. </p> <p> Given a comparative question, retrieve and rank documents from the ClueWeb12 that help to answer the comparative question. </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://webis.de/events/touche-21/shared-task-2.html”>Task 2 website</a></li> <li><a href=”https://webis.de/events/touche-21/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-85251-1_28”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI8FDfYnzcjbsf26RIatNgM3”>Workshop videos</a></li> </ul>

Dataset irds.clueweb12.touche-2021-task-2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2021 is the second lab on argument retrieval at CLEF 2021 featuring two tasks. </p> <p> Given a comparative question, retrieve and rank documents from the ClueWeb12 that help to answer the comparative question. </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://webis.de/events/touche-21/shared-task-2.html”>Task 2 website</a></li> <li><a href=”https://webis.de/events/touche-21/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-85251-1_28”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI8FDfYnzcjbsf26RIatNgM3”>Workshop videos</a></li> </ul>

Dataset irds.clueweb12.touche-2021-task-2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2021 is the second lab on argument retrieval at CLEF 2021 featuring two tasks. </p> <p> Given a comparative question, retrieve and rank documents from the ClueWeb12 that help to answer the comparative question. </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <ul> <li><a href=”https://webis.de/events/touche-21/shared-task-2.html”>Task 2 website</a></li> <li><a href=”https://webis.de/events/touche-21/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-85251-1_28”>Overview paper</a></li> <li><a href=”https://www.youtube.com/playlist?list=PLgD1TOdHQCI8FDfYnzcjbsf26RIatNgM3”>Workshop videos</a></li> </ul>

clueweb12/b13

<p> Official subset of the ClueWeb12 datasets with 52M web pages. </p>

Dataset irds.clueweb12.b13.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Official subset of the ClueWeb12 datasets with 52M web pages. </p>

Dataset irds.clueweb12.b13.clef-ehealth.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The CLEF eHealth 2016-17 IR dataset. Contains consumer health queries and judgments containing trustworthiness and understandability scores, in addition to the normal relevance assessments. </p> <p> This dataset contains the combined 2016 and 2017 relevance judgments, since the same queries were used in the two year. The assessment year can be distinguished using iteration (2016 is iteration 0, 2017 is iteration 1). </p> <ul> <li><a href=”https://sites.google.com/site/clefehealth2016/task-3”>2016 shared task site</a></li> <li><a href=”https://sites.google.com/site/clefehealth2017/task-3”>2017 shared task site</a></li> <li><a href=”http://ceur-ws.org/Vol-1609/16090015.pdf”>2016 shared task paper</a></li> <li><a href=”http://ceur-ws.org/Vol-1866/invited_paper_16.pdf”>2017 shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.clef-ehealth.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The CLEF eHealth 2016-17 IR dataset. Contains consumer health queries and judgments containing trustworthiness and understandability scores, in addition to the normal relevance assessments. </p> <p> This dataset contains the combined 2016 and 2017 relevance judgments, since the same queries were used in the two year. The assessment year can be distinguished using iteration (2016 is iteration 0, 2017 is iteration 1). </p> <ul> <li><a href=”https://sites.google.com/site/clefehealth2016/task-3”>2016 shared task site</a></li> <li><a href=”https://sites.google.com/site/clefehealth2017/task-3”>2017 shared task site</a></li> <li><a href=”http://ceur-ws.org/Vol-1609/16090015.pdf”>2016 shared task paper</a></li> <li><a href=”http://ceur-ws.org/Vol-1866/invited_paper_16.pdf”>2017 shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.clef-ehealth

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The CLEF eHealth 2016-17 IR dataset. Contains consumer health queries and judgments containing trustworthiness and understandability scores, in addition to the normal relevance assessments. </p> <p> This dataset contains the combined 2016 and 2017 relevance judgments, since the same queries were used in the two year. The assessment year can be distinguished using iteration (2016 is iteration 0, 2017 is iteration 1). </p> <ul> <li><a href=”https://sites.google.com/site/clefehealth2016/task-3”>2016 shared task site</a></li> <li><a href=”https://sites.google.com/site/clefehealth2017/task-3”>2017 shared task site</a></li> <li><a href=”http://ceur-ws.org/Vol-1609/16090015.pdf”>2016 shared task paper</a></li> <li><a href=”http://ceur-ws.org/Vol-1866/invited_paper_16.pdf”>2017 shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.clef-ehealth.cs.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Czech. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.cs.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Czech. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.cs

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Czech. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.de.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to German. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.de.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to German. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.de

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to German. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.fr.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to French. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.fr.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to French. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.fr

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to French. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.hu.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Hungarian. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.hu.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Hungarian. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.hu

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Hungarian. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.pl.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Polish. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.pl.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Polish. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.pl

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Polish. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.sv.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Swedish. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.sv.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Swedish. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.clef-ehealth.sv

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The CLEF eHealth 2016-17 IR dataset, with queries professionally translataed to Swedish. See <a class=”ds-ref”>clueweb12/b13/clef-ehealth</a> for more details. </p>

Dataset irds.clueweb12.b13.ntcir-www-1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The NTCIR-13 We Want Web (WWW) 1 ad-hoc ranking benchmark. Contains 100 queries with deep relevance judgments (avg 255 per query). Judgments aggregated from two assessors. Note that the qrels contain additional judgments from the NTCIR-14 CENTRE track. </p> <ul> <li><a href=”http://www.thuir.cn/ntcirwww/”>Shared task site</a></li> <li><a href=”http://www.thuir.cn/ntcirwww/files/ntcir13wwwov.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.ntcir-www-1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The NTCIR-13 We Want Web (WWW) 1 ad-hoc ranking benchmark. Contains 100 queries with deep relevance judgments (avg 255 per query). Judgments aggregated from two assessors. Note that the qrels contain additional judgments from the NTCIR-14 CENTRE track. </p> <ul> <li><a href=”http://www.thuir.cn/ntcirwww/”>Shared task site</a></li> <li><a href=”http://www.thuir.cn/ntcirwww/files/ntcir13wwwov.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.ntcir-www-1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The NTCIR-13 We Want Web (WWW) 1 ad-hoc ranking benchmark. Contains 100 queries with deep relevance judgments (avg 255 per query). Judgments aggregated from two assessors. Note that the qrels contain additional judgments from the NTCIR-14 CENTRE track. </p> <ul> <li><a href=”http://www.thuir.cn/ntcirwww/”>Shared task site</a></li> <li><a href=”http://www.thuir.cn/ntcirwww/files/ntcir13wwwov.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.ntcir-www-2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The NTCIR-14 We Want Web (WWW) 2 ad-hoc ranking benchmark. Contains 80 queries with deep relevance judgments (avg 345 per query). Judgments aggregated from two assessors. </p> <ul> <li><a href=”http://www.thuir.cn/ntcirwww2/”>Shared task site</a></li> <li><a href=”http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings14/pdf/ntcir/01-NTCIR14-OV-WWW-MaoJ.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.ntcir-www-2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The NTCIR-14 We Want Web (WWW) 2 ad-hoc ranking benchmark. Contains 80 queries with deep relevance judgments (avg 345 per query). Judgments aggregated from two assessors. </p> <ul> <li><a href=”http://www.thuir.cn/ntcirwww2/”>Shared task site</a></li> <li><a href=”http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings14/pdf/ntcir/01-NTCIR14-OV-WWW-MaoJ.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.ntcir-www-2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The NTCIR-14 We Want Web (WWW) 2 ad-hoc ranking benchmark. Contains 80 queries with deep relevance judgments (avg 345 per query). Judgments aggregated from two assessors. </p> <ul> <li><a href=”http://www.thuir.cn/ntcirwww2/”>Shared task site</a></li> <li><a href=”http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings14/pdf/ntcir/01-NTCIR14-OV-WWW-MaoJ.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.ntcir-www-3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The NTCIR-15 We Want Web (WWW) 3 ad-hoc ranking benchmark. Contains 160 queries with deep relevance judgments (to be released). 80 of the queries are from <a class=”ds-ref”>clueweb12/b13/ntcir-www-2</a>. </p> <ul> <li><a href=”http://sakailab.com/www3/”>Shared task site</a></li> </ul>

Dataset irds.clueweb12.b13.trec-misinfo-2019.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Medical Misinformation 2019 dataset. </p> <ul> <li><a href=”https://trec.nist.gov/data/misinfo2019.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.D.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.trec-misinfo-2019.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Medical Misinformation 2019 dataset. </p> <ul> <li><a href=”https://trec.nist.gov/data/misinfo2019.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.D.pdf”>Shared task paper</a></li> </ul>

Dataset irds.clueweb12.b13.trec-misinfo-2019

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Medical Misinformation 2019 dataset. </p> <ul> <li><a href=”https://trec.nist.gov/data/misinfo2019.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.D.pdf”>Shared task paper</a></li> </ul>

CODEC

<p> CODEC Document Ranking sub-task. </p> <ul> <li>Documents: curated web articles</li> <li>Queries: challenging, entity-focused queries</li> <li><a href=”https://github.com/grill-lab/CODEC”>Task Repository</a></li> <li>See also: <a class=”ds-ref”>kilt/codec</a>, the entity ranking subtask</li> </ul>

Dataset irds.codec.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> CODEC Document Ranking sub-task. </p> <ul> <li>Documents: curated web articles</li> <li>Queries: challenging, entity-focused queries</li> <li><a href=”https://github.com/grill-lab/CODEC”>Task Repository</a></li> <li>See also: <a class=”ds-ref”>kilt/codec</a>, the entity ranking subtask</li> </ul>

Dataset irds.codec.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> CODEC Document Ranking sub-task. </p> <ul> <li>Documents: curated web articles</li> <li>Queries: challenging, entity-focused queries</li> <li><a href=”https://github.com/grill-lab/CODEC”>Task Repository</a></li> <li>See also: <a class=”ds-ref”>kilt/codec</a>, the entity ranking subtask</li> </ul>

Dataset irds.codec.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> CODEC Document Ranking sub-task. </p> <ul> <li>Documents: curated web articles</li> <li>Queries: challenging, entity-focused queries</li> <li><a href=”https://github.com/grill-lab/CODEC”>Task Repository</a></li> <li>See also: <a class=”ds-ref”>kilt/codec</a>, the entity ranking subtask</li> </ul>

Dataset irds.codec

→ datamaestro_text.datasets.irds.data.Adhoc

<p> CODEC Document Ranking sub-task. </p> <ul> <li>Documents: curated web articles</li> <li>Queries: challenging, entity-focused queries</li> <li><a href=”https://github.com/grill-lab/CODEC”>Task Repository</a></li> <li>See also: <a class=”ds-ref”>kilt/codec</a>, the entity ranking subtask</li> </ul>

Dataset irds.codec.economics.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about economics. </p>

Dataset irds.codec.economics.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about economics. </p>

Dataset irds.codec.economics

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about economics. </p>

Dataset irds.codec.history.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about history. </p>

Dataset irds.codec.history.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about history. </p>

Dataset irds.codec.history

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about history. </p>

Dataset irds.codec.politics.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about politics. </p>

Dataset irds.codec.politics.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about politics. </p>

Dataset irds.codec.politics

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about politics. </p>

CORD-19

<p> Collection of scientific articles related to COVID-19. </p> <p> Uses the 2020-07-16 version of the dataset, corresponding to the “complete” collection used for TREC COVID. </p> <p> Note that this version of the document collection only provides article meta-data. To get the full text, use <a class=”ds-ref”>cord19/fulltext</a>. </p> <ul> <li><a href=”https://www.semanticscholar.org/cord19”>Document collection site</a></li> </ul>

Dataset irds.cord19.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Collection of scientific articles related to COVID-19. </p> <p> Uses the 2020-07-16 version of the dataset, corresponding to the “complete” collection used for TREC COVID. </p> <p> Note that this version of the document collection only provides article meta-data. To get the full text, use <a class=”ds-ref”>cord19/fulltext</a>. </p> <ul> <li><a href=”https://www.semanticscholar.org/cord19”>Document collection site</a></li> </ul>

Dataset irds.cord19.trec-covid.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The Complete TREC COVID collection. Queries related to COVID-19, including deep relevance judgments. </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The Complete TREC COVID collection. Queries related to COVID-19, including deep relevance judgments. </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The Complete TREC COVID collection. Queries related to COVID-19, including deep relevance judgments. </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round5.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Round 5 of the TREC COVID task. Includes 50 queries related to COVID-19. This uses the “2020-07-16” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round5.html”>Round 5 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round5.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Round 5 of the TREC COVID task. Includes 50 queries related to COVID-19. This uses the “2020-07-16” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round5.html”>Round 5 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round5

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Round 5 of the TREC COVID task. Includes 50 queries related to COVID-19. This uses the “2020-07-16” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round5.html”>Round 5 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

cord19/fulltext

<p> Version of <a class=”ds-ref”>cord19</a> dataset that includes article full texts. This dataset takes longer to load than the version that only includes article meata-data. </p>

Dataset irds.cord19.fulltext.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>cord19</a> dataset that includes article full texts. This dataset takes longer to load than the version that only includes article meata-data. </p>

Dataset irds.cord19.fulltext.trec-covid.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>cord19/trec-covid</a> dataset that includes article full texts. This dataset takes longer to load than the version that only includes article meata-data. </p> <p> Queries and qrels are the same as <a class=”ds-ref”>cord19/trec-covid</a>; it just uses the extended documents from <a class=”ds-ref”>cord19/fulltext</a>. </p>

Dataset irds.cord19.fulltext.trec-covid.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>cord19/trec-covid</a> dataset that includes article full texts. This dataset takes longer to load than the version that only includes article meata-data. </p> <p> Queries and qrels are the same as <a class=”ds-ref”>cord19/trec-covid</a>; it just uses the extended documents from <a class=”ds-ref”>cord19/fulltext</a>. </p>

Dataset irds.cord19.fulltext.trec-covid

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>cord19/trec-covid</a> dataset that includes article full texts. This dataset takes longer to load than the version that only includes article meata-data. </p> <p> Queries and qrels are the same as <a class=”ds-ref”>cord19/trec-covid</a>; it just uses the extended documents from <a class=”ds-ref”>cord19/fulltext</a>. </p>

cord19/trec-covid/round1

<p> Round 1 of the TREC COVID task. Includes 30 queries related to COVID-19. This uses the “2020-04-10” version of the collection. </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round1.html”>Round 1 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round1.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Round 1 of the TREC COVID task. Includes 30 queries related to COVID-19. This uses the “2020-04-10” version of the collection. </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round1.html”>Round 1 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Round 1 of the TREC COVID task. Includes 30 queries related to COVID-19. This uses the “2020-04-10” version of the collection. </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round1.html”>Round 1 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Round 1 of the TREC COVID task. Includes 30 queries related to COVID-19. This uses the “2020-04-10” version of the collection. </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round1.html”>Round 1 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Round 1 of the TREC COVID task. Includes 30 queries related to COVID-19. This uses the “2020-04-10” version of the collection. </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round1.html”>Round 1 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

cord19/trec-covid/round2

<p> Round 2 of the TREC COVID task. Includes 35 queries related to COVID-19. This uses the “2020-05-01” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round2.html”>Round 2 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round2.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Round 2 of the TREC COVID task. Includes 35 queries related to COVID-19. This uses the “2020-05-01” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round2.html”>Round 2 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Round 2 of the TREC COVID task. Includes 35 queries related to COVID-19. This uses the “2020-05-01” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round2.html”>Round 2 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Round 2 of the TREC COVID task. Includes 35 queries related to COVID-19. This uses the “2020-05-01” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round2.html”>Round 2 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Round 2 of the TREC COVID task. Includes 35 queries related to COVID-19. This uses the “2020-05-01” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round2.html”>Round 2 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

cord19/trec-covid/round3

<p> Round 3 of the TREC COVID task. Includes 40 queries related to COVID-19. This uses the “2020-05-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round3.html”>Round 3 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round3.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Round 3 of the TREC COVID task. Includes 40 queries related to COVID-19. This uses the “2020-05-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round3.html”>Round 3 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Round 3 of the TREC COVID task. Includes 40 queries related to COVID-19. This uses the “2020-05-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round3.html”>Round 3 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Round 3 of the TREC COVID task. Includes 40 queries related to COVID-19. This uses the “2020-05-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round3.html”>Round 3 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round3

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Round 3 of the TREC COVID task. Includes 40 queries related to COVID-19. This uses the “2020-05-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round3.html”>Round 3 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

cord19/trec-covid/round4

<p> Round 4 of the TREC COVID task. Includes 45 queries related to COVID-19. This uses the “2020-06-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round4.html”>Round 4 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round4.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Round 4 of the TREC COVID task. Includes 45 queries related to COVID-19. This uses the “2020-06-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round4.html”>Round 4 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round4.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Round 4 of the TREC COVID task. Includes 45 queries related to COVID-19. This uses the “2020-06-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round4.html”>Round 4 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round4.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Round 4 of the TREC COVID task. Includes 45 queries related to COVID-19. This uses the “2020-06-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round4.html”>Round 4 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Dataset irds.cord19.trec-covid.round4

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Round 4 of the TREC COVID task. Includes 45 queries related to COVID-19. This uses the “2020-06-19” version of the collection. </p> <p> Note that the qrels do not contain results from the prior round(s). Use the “complete” version for this setting (<a class=”ds-ref”>cord19/trec-covid</a>). </p> <ul> <li><a href=”https://ir.nist.gov/covidSubmit/round4.html”>Round 4 Guidelines</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/index.html”>Shared task site</a></li> <li><a href=”https://ir.nist.gov/covidSubmit/papers/Forum_TRECCOVID1.pdf”>Shared task paper</a></li> </ul>

Cranfield

<p> A small corpus of 1,400 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language questions</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/cran/”>Dataset Information</a></li> </ul>

Dataset irds.cranfield.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A small corpus of 1,400 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language questions</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/cran/”>Dataset Information</a></li> </ul>

Dataset irds.cranfield.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A small corpus of 1,400 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language questions</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/cran/”>Dataset Information</a></li> </ul>

Dataset irds.cranfield.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A small corpus of 1,400 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language questions</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/cran/”>Dataset Information</a></li> </ul>

Dataset irds.cranfield

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A small corpus of 1,400 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language questions</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/cran/”>Dataset Information</a></li> </ul>

CSL

<p> The CSL dataset, used for the TREC NueCLIR technical document task. </p>

Dataset irds.csl.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The CSL dataset, used for the TREC NueCLIR technical document task. </p>

Dataset irds.csl.trec-2023.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC NeuCLIR 2023 technical documen task. </p>

Dataset irds.csl.trec-2023.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC NeuCLIR 2023 technical documen task. </p>

Dataset irds.csl.trec-2023

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC NeuCLIR 2023 technical documen task. </p>

disks45/nocr

<p> A version of <a class=”ds-ref”>disks45</a> without the Congressional Record. This is the typical setting for tasks like TREC 7, TREC 8, and TREC Robust 2004. </p>

Dataset irds.disks45.nocr.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of <a class=”ds-ref”>disks45</a> without the Congressional Record. This is the typical setting for tasks like TREC 7, TREC 8, and TREC Robust 2004. </p>

Dataset irds.disks45.nocr.trec-robust-2004.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Robust retrieval task focuses on “improving the consistency of retrieval technology by focusing on poorly performing topics.” </p> <p> The TREC Robust document collection is from TREC disks 4 and 5. Due to the copyrighted nature of the documents, this collection is for research use only, which requires agreements to be filed with NIST. See details <a href=”https://trec.nist.gov/data/cd45/index.html”>here</a>. </p> <ul> <li>Documents: News articles</li> <li>Queries: keyword queries, descriptions, narratives</li> <li>Relevance: Deep judgments</li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/ROBUST.OVERVIEW.pdf”>Task Overview Paper</a></li> <li>See also: <a class=”ds-ref”>aquaint/trec-robust-2005</a></li> </ul>

Dataset irds.disks45.nocr.trec-robust-2004.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Robust retrieval task focuses on “improving the consistency of retrieval technology by focusing on poorly performing topics.” </p> <p> The TREC Robust document collection is from TREC disks 4 and 5. Due to the copyrighted nature of the documents, this collection is for research use only, which requires agreements to be filed with NIST. See details <a href=”https://trec.nist.gov/data/cd45/index.html”>here</a>. </p> <ul> <li>Documents: News articles</li> <li>Queries: keyword queries, descriptions, narratives</li> <li>Relevance: Deep judgments</li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/ROBUST.OVERVIEW.pdf”>Task Overview Paper</a></li> <li>See also: <a class=”ds-ref”>aquaint/trec-robust-2005</a></li> </ul>

Dataset irds.disks45.nocr.trec-robust-2004

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Robust retrieval task focuses on “improving the consistency of retrieval technology by focusing on poorly performing topics.” </p> <p> The TREC Robust document collection is from TREC disks 4 and 5. Due to the copyrighted nature of the documents, this collection is for research use only, which requires agreements to be filed with NIST. See details <a href=”https://trec.nist.gov/data/cd45/index.html”>here</a>. </p> <ul> <li>Documents: News articles</li> <li>Queries: keyword queries, descriptions, narratives</li> <li>Relevance: Deep judgments</li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/ROBUST.OVERVIEW.pdf”>Task Overview Paper</a></li> <li>See also: <a class=”ds-ref”>aquaint/trec-robust-2005</a></li> </ul>

Dataset irds.disks45.nocr.trec-robust-2004.fold1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Robust04 Fold 1 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Robust04 Fold 1 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold1

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Robust04 Fold 1 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Robust04 Fold 2 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Robust04 Fold 2 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold2

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Robust04 Fold 2 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Robust04 Fold 3 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Robust04 Fold 3 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold3

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Robust04 Fold 3 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold4.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Robust04 Fold 4 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold4.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Robust04 Fold 4 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold4

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Robust04 Fold 4 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold5.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Robust04 Fold 5 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold5.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Robust04 Fold 5 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec-robust-2004.fold5

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Robust04 Fold 5 (Title) proposed by Huston &amp; Croft (2014) and used in numerous works</p>

Dataset irds.disks45.nocr.trec7.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC 7 Adhoc Retrieval track. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec7/papers/overview_7.pdf.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.disks45.nocr.trec7.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC 7 Adhoc Retrieval track. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec7/papers/overview_7.pdf.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.disks45.nocr.trec7

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC 7 Adhoc Retrieval track. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec7/papers/overview_7.pdf.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.disks45.nocr.trec8.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC 8 Adhoc Retrieval track. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec8/papers/overview_8.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.disks45.nocr.trec8.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC 8 Adhoc Retrieval track. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec8/papers/overview_8.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.disks45.nocr.trec8

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC 8 Adhoc Retrieval track. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec8/papers/overview_8.pdf”>Task Overview Paper</a></li> </ul>

DPR Wiki100

<p> A wikipedia dump from 20 December, 2018, split into passages of 100 words. Used in experiments in the DPR paper (and other subsequent works) for retrieval experiments over Q&amp;A collections. </p> <ul> <li><a href=”https://arxiv.org/pdf/2004.04906.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/facebookresearch/DPR”>Repository</a></li> </ul>

Dataset irds.dpr-w100.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A wikipedia dump from 20 December, 2018, split into passages of 100 words. Used in experiments in the DPR paper (and other subsequent works) for retrieval experiments over Q&amp;A collections. </p> <ul> <li><a href=”https://arxiv.org/pdf/2004.04906.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/facebookresearch/DPR”>Repository</a></li> </ul>

Dataset irds.dpr-w100.natural-questions.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Dev subset from the Natural Questions Q&amp;A collection. This differs from the <a class=”ds-ref”>natural-questions/dev</a> dataset in that it uses the full Wikipedia dump and additional filtering (described in the DPR paper) was applied. </p> <ul> <li>See also: <a class=”ds-ref”>natural-questions</a></li> </ul>

Dataset irds.dpr-w100.natural-questions.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Dev subset from the Natural Questions Q&amp;A collection. This differs from the <a class=”ds-ref”>natural-questions/dev</a> dataset in that it uses the full Wikipedia dump and additional filtering (described in the DPR paper) was applied. </p> <ul> <li>See also: <a class=”ds-ref”>natural-questions</a></li> </ul>

Dataset irds.dpr-w100.natural-questions.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Dev subset from the Natural Questions Q&amp;A collection. This differs from the <a class=”ds-ref”>natural-questions/dev</a> dataset in that it uses the full Wikipedia dump and additional filtering (described in the DPR paper) was applied. </p> <ul> <li>See also: <a class=”ds-ref”>natural-questions</a></li> </ul>

Dataset irds.dpr-w100.natural-questions.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training subset from the Natural Questions Q&amp;A collection. This differs from the <a class=”ds-ref”>natural-questions/train</a> dataset in that it uses the full Wikipedia dump and additional filtering (described in the DPR paper) was applied. </p> <ul> <li>See also: <a class=”ds-ref”>natural-questions</a></li> </ul>

Dataset irds.dpr-w100.natural-questions.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training subset from the Natural Questions Q&amp;A collection. This differs from the <a class=”ds-ref”>natural-questions/train</a> dataset in that it uses the full Wikipedia dump and additional filtering (described in the DPR paper) was applied. </p> <ul> <li>See also: <a class=”ds-ref”>natural-questions</a></li> </ul>

Dataset irds.dpr-w100.natural-questions.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training subset from the Natural Questions Q&amp;A collection. This differs from the <a class=”ds-ref”>natural-questions/train</a> dataset in that it uses the full Wikipedia dump and additional filtering (described in the DPR paper) was applied. </p> <ul> <li>See also: <a class=”ds-ref”>natural-questions</a></li> </ul>

Dataset irds.dpr-w100.trivia-qa.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Dev subset from the Trivia QA dataset. Differing from the official Trivia QA collection, this uses the DPR Wikipedia dump as the source collection. Refer to the DPR paper for more details. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P17-1147.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cs.washington.edu/triviaqa/”>Dataset website</a></li> </ul>

Dataset irds.dpr-w100.trivia-qa.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Dev subset from the Trivia QA dataset. Differing from the official Trivia QA collection, this uses the DPR Wikipedia dump as the source collection. Refer to the DPR paper for more details. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P17-1147.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cs.washington.edu/triviaqa/”>Dataset website</a></li> </ul>

Dataset irds.dpr-w100.trivia-qa.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Dev subset from the Trivia QA dataset. Differing from the official Trivia QA collection, this uses the DPR Wikipedia dump as the source collection. Refer to the DPR paper for more details. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P17-1147.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cs.washington.edu/triviaqa/”>Dataset website</a></li> </ul>

Dataset irds.dpr-w100.trivia-qa.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training subset from the Trivia QA dataset. Differing from the official Trivia QA collection, this uses the DPR Wikipedia dump as the source collection. Refer to the DPR paper for more details. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P17-1147.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cs.washington.edu/triviaqa/”>Dataset website</a></li> </ul>

Dataset irds.dpr-w100.trivia-qa.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training subset from the Trivia QA dataset. Differing from the official Trivia QA collection, this uses the DPR Wikipedia dump as the source collection. Refer to the DPR paper for more details. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P17-1147.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cs.washington.edu/triviaqa/”>Dataset website</a></li> </ul>

Dataset irds.dpr-w100.trivia-qa.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training subset from the Trivia QA dataset. Differing from the official Trivia QA collection, this uses the DPR Wikipedia dump as the source collection. Refer to the DPR paper for more details. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P17-1147.pdf”>Dataset paper</a></li> <li><a href=”http://nlp.cs.washington.edu/triviaqa/”>Dataset website</a></li> </ul>

CodeSearchNet

<p> A benchmark for semantic code search. Uses </p> <ul> <li>Documents: Code functions in python, java, go, php, ruby, and javascript</li> <li>Queries: Inferred from docstrings, or </li> <li><a href=”https://arxiv.org/pdf/1909.09436.pdf”>Dataset Paper</a></li> <li><a href=”https://wandb.ai/github/codesearchnet/benchmark/leaderboard”>Challenge Task Leaderboard</a></li> </ul>

Dataset irds.codesearchnet.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A benchmark for semantic code search. Uses </p> <ul> <li>Documents: Code functions in python, java, go, php, ruby, and javascript</li> <li>Queries: Inferred from docstrings, or </li> <li><a href=”https://arxiv.org/pdf/1909.09436.pdf”>Dataset Paper</a></li> <li><a href=”https://wandb.ai/github/codesearchnet/benchmark/leaderboard”>Challenge Task Leaderboard</a></li> </ul>

Dataset irds.codesearchnet.challenge.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official challenge set, with keyword queries and deep relevance assessments. </p>

Dataset irds.codesearchnet.challenge.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official challenge set, with keyword queries and deep relevance assessments. </p>

Dataset irds.codesearchnet.challenge

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official challenge set, with keyword queries and deep relevance assessments. </p>

Dataset irds.codesearchnet.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test set, using queries inferred from docstrings. </p>

Dataset irds.codesearchnet.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test set, using queries inferred from docstrings. </p>

Dataset irds.codesearchnet.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test set, using queries inferred from docstrings. </p>

Dataset irds.codesearchnet.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set, using queries inferred from docstrings. </p>

Dataset irds.codesearchnet.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set, using queries inferred from docstrings. </p>

Dataset irds.codesearchnet.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set, using queries inferred from docstrings. </p>

Dataset irds.codesearchnet.valid.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official validation set, using queries inferred from docstrings. </p>

Dataset irds.codesearchnet.valid.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official validation set, using queries inferred from docstrings. </p>

Dataset irds.codesearchnet.valid

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official validation set, using queries inferred from docstrings. </p>

GOV

<p> GOV web document collection. Used for early TREC Web Tracks. Not to be confused with <a class=”ds-ref”>gov2</a>. </p> <p> The dataset is obtained for a fee from UoG, and is shipped as a hard drive. More information is provided <a href=”http://ir.dcs.gla.ac.uk/test_collections/access_to_data.html”>here</a>. </p> <ul> <li><a href=”http://ir.dcs.gla.ac.uk/test_collections/gov2-summary.htm”>Document collection site</a></li> </ul>

Dataset irds.gov.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> GOV web document collection. Used for early TREC Web Tracks. Not to be confused with <a class=”ds-ref”>gov2</a>. </p> <p> The dataset is obtained for a fee from UoG, and is shipped as a hard drive. More information is provided <a href=”http://ir.dcs.gla.ac.uk/test_collections/access_to_data.html”>here</a>. </p> <ul> <li><a href=”http://ir.dcs.gla.ac.uk/test_collections/gov2-summary.htm”>Document collection site</a></li> </ul>

Dataset irds.gov.trec-web-2002.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2002 ad-hoc ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t11.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/WEB.OVER.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2002.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2002 ad-hoc ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t11.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/WEB.OVER.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2002

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2002 ad-hoc ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t11.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/WEB.OVER.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2002.named-page.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2002 named page ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t11.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/WEB.OVER.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2002.named-page.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2002 named page ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t11.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/WEB.OVER.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2002.named-page

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2002 named page ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t11.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/WEB.OVER.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2003.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2003 ad-hoc ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t12.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2003.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2003 ad-hoc ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t12.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2003

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2003 ad-hoc ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t12.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2003.named-page.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2003 named page ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t12.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2003.named-page.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2003 named page ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t12.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2003.named-page

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2003 named page ranking benchmark. </p> <ul> <li><a href=”https://trec.nist.gov/data/t12.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2004.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Web Track 2004 ad-hoc ranking benchmark. </p> <p> Queries include a combination of topic distillation, homepage finding, and named page finding. </p> <ul> <li><a href=”https://trec.nist.gov/data/t13.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2004.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Web Track 2004 ad-hoc ranking benchmark. </p> <p> Queries include a combination of topic distillation, homepage finding, and named page finding. </p> <ul> <li><a href=”https://trec.nist.gov/data/t13.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov.trec-web-2004

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Web Track 2004 ad-hoc ranking benchmark. </p> <p> Queries include a combination of topic distillation, homepage finding, and named page finding. </p> <ul> <li><a href=”https://trec.nist.gov/data/t13.web.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec12/papers/WEB.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

GOV2

<p> GOV2 web document collection. Used for the TREC Terabyte Track. </p> <p> The dataset is obtained for a fee from UoG, and is shipped as a hard drive. More information is provided <a href=”http://ir.dcs.gla.ac.uk/test_collections/access_to_data.html”>here</a>. </p> <ul> <li><a href=”http://ir.dcs.gla.ac.uk/test_collections/gov2-summary.htm”>Document collection site</a></li> </ul>

Dataset irds.gov2.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> GOV2 web document collection. Used for the TREC Terabyte Track. </p> <p> The dataset is obtained for a fee from UoG, and is shipped as a hard drive. More information is provided <a href=”http://ir.dcs.gla.ac.uk/test_collections/access_to_data.html”>here</a>. </p> <ul> <li><a href=”http://ir.dcs.gla.ac.uk/test_collections/gov2-summary.htm”>Document collection site</a></li> </ul>

Dataset irds.gov2.trec-mq-2007.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> TREC 2007 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query07.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec16/papers/1MQ.OVERVIEW16.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-mq-2007.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> TREC 2007 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query07.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec16/papers/1MQ.OVERVIEW16.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-mq-2007

→ datamaestro_text.datasets.irds.data.Adhoc

<p> TREC 2007 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query07.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec16/papers/1MQ.OVERVIEW16.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-mq-2008.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> TREC 2008 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query08.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec17/papers/MQ.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-mq-2008.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> TREC 2008 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query08.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec17/papers/MQ.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-mq-2008

→ datamaestro_text.datasets.irds.data.Adhoc

<p> TREC 2008 Million Query track. </p> <ul> <li><a href=”https://trec.nist.gov/data/million.query08.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec17/papers/MQ.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2004.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Terabyte Track 2004 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte04.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/TERA.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2004.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Terabyte Track 2004 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte04.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/TERA.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2004

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Terabyte Track 2004 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte04.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec13/papers/TERA.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Terabyte Track 2005 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Terabyte Track 2005 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Terabyte Track 2005 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005.efficiency.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Terabyte Track 2005 efficiency ranking benchmark. Contains 50,000 queries from a search engine, including the 50 topics from <a class=”ds-ref”>gov2/trec-tb-2005</a>. Only the 50 topics have judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005.efficiency.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Terabyte Track 2005 efficiency ranking benchmark. Contains 50,000 queries from a search engine, including the 50 topics from <a class=”ds-ref”>gov2/trec-tb-2005</a>. Only the 50 topics have judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005.efficiency

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Terabyte Track 2005 efficiency ranking benchmark. Contains 50,000 queries from a search engine, including the 50 topics from <a class=”ds-ref”>gov2/trec-tb-2005</a>. Only the 50 topics have judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005.named-page.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Terabyte Track 2005 named page ranking benchmark. Contains 252 queries with titles that resemble bookmark labels. Relevance judgments include near-duplicate pages and other pages that may satisfy the bookmark label. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005.named-page.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Terabyte Track 2005 named page ranking benchmark. Contains 252 queries with titles that resemble bookmark labels. Relevance judgments include near-duplicate pages and other pages that may satisfy the bookmark label. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2005.named-page

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Terabyte Track 2005 named page ranking benchmark. Contains 252 queries with titles that resemble bookmark labels. Relevance judgments include near-duplicate pages and other pages that may satisfy the bookmark label. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Terabyte Track 2006 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte06.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/TERA06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Terabyte Track 2006 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte06.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/TERA06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Terabyte Track 2006 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte06.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/TERA06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006.efficiency.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Terabyte Track 2006 efficiency ranking benchmark. Contains 100,000 queries from a search engine, including the 50 topics from <a class=”ds-ref”>gov2/trec-tb-2006</a>. Only the 50 topics have judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006.efficiency.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Terabyte Track 2006 efficiency ranking benchmark. Contains 100,000 queries from a search engine, including the 50 topics from <a class=”ds-ref”>gov2/trec-tb-2006</a>. Only the 50 topics have judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006.efficiency

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Terabyte Track 2006 efficiency ranking benchmark. Contains 100,000 queries from a search engine, including the 50 topics from <a class=”ds-ref”>gov2/trec-tb-2006</a>. Only the 50 topics have judgments. </p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte05.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec14/papers/TERABYTE.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006.efficiency.10k.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Small stream from <a class=”ds-ref”>gov2/trec-tb-2006/efficiency</a>, with 10,000 queries. </p>

Dataset irds.gov2.trec-tb-2006.efficiency.stream1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Stream 1 of <a class=”ds-ref”>gov2/trec-tb-2006/efficiency</a> (25,000 queries). </p>

Dataset irds.gov2.trec-tb-2006.efficiency.stream2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Stream 2 of <a class=”ds-ref”>gov2/trec-tb-2006/efficiency</a> (25,000 queries). </p>

Dataset irds.gov2.trec-tb-2006.efficiency.stream3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Stream 3 of <a class=”ds-ref”>gov2/trec-tb-2006/efficiency</a> (25,000 queries). </p>

Dataset irds.gov2.trec-tb-2006.efficiency.stream3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Stream 3 of <a class=”ds-ref”>gov2/trec-tb-2006/efficiency</a> (25,000 queries). </p>

Dataset irds.gov2.trec-tb-2006.efficiency.stream3

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Stream 3 of <a class=”ds-ref”>gov2/trec-tb-2006/efficiency</a> (25,000 queries). </p>

Dataset irds.gov2.trec-tb-2006.efficiency.stream4.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Stream 4 of <a class=”ds-ref”>gov2/trec-tb-2006/efficiency</a> (25,000 queries). </p>

Dataset irds.gov2.trec-tb-2006.named-page.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Terabyte Track 2006 named page ranking benchmark. Contains 181 queries with titles that resemble bookmark labels. Relevance judgments include near-duplicate pages and other pages that may satisfy the bookmark label.</p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte06.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/TERA06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006.named-page.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Terabyte Track 2006 named page ranking benchmark. Contains 181 queries with titles that resemble bookmark labels. Relevance judgments include near-duplicate pages and other pages that may satisfy the bookmark label.</p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte06.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/TERA06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Dataset irds.gov2.trec-tb-2006.named-page

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Terabyte Track 2006 named page ranking benchmark. Contains 181 queries with titles that resemble bookmark labels. Relevance judgments include near-duplicate pages and other pages that may satisfy the bookmark label.</p> <ul> <li><a href=”https://trec.nist.gov/data/terabyte06.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec15/papers/TERA06.OVERVIEW.pdf”>Shared task paper</a></li> </ul>

Istella22

<p> The Istella22 dataset facilitates comparisions between traditional and neural learning-to-rank by including query and document text along with LTR features (not included in ir_datasets). </p> <p> Note that to use the dataset, you must <b>read and accept</b> the <a href=”https://www.istella.ai/dataset/Istella22-LicenseAgreement.txt”>Istella22 License Agreement</a>. By using the dataset, you agree to be bound by the terms of the license: the <b>Istella dataset is solely for non-commercial use</b>. </p> <ul> <li><a href=”https://dl.acm.org/doi/abs/10.1145/3477495.3531740”>Paper</a></li> <li><a href=”https://istella.ai/data/istella22-dataset/”>Website</a></li> </ul>

Dataset irds.istella22.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Istella22 dataset facilitates comparisions between traditional and neural learning-to-rank by including query and document text along with LTR features (not included in ir_datasets). </p> <p> Note that to use the dataset, you must <b>read and accept</b> the <a href=”https://www.istella.ai/dataset/Istella22-LicenseAgreement.txt”>Istella22 License Agreement</a>. By using the dataset, you agree to be bound by the terms of the license: the <b>Istella dataset is solely for non-commercial use</b>. </p> <ul> <li><a href=”https://dl.acm.org/doi/abs/10.1145/3477495.3531740”>Paper</a></li> <li><a href=”https://istella.ai/data/istella22-dataset/”>Website</a></li> </ul>

Dataset irds.istella22.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test query set. </p>

Dataset irds.istella22.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test query set. </p>

Dataset irds.istella22.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test query set. </p>

Dataset irds.istella22.test.fold1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test query set. </p>

Dataset irds.istella22.test.fold1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test query set. </p>

Dataset irds.istella22.test.fold1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test query set. </p>

Dataset irds.istella22.test.fold2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test query set. </p>

Dataset irds.istella22.test.fold2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test query set. </p>

Dataset irds.istella22.test.fold2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test query set. </p>

Dataset irds.istella22.test.fold3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test query set. </p>

Dataset irds.istella22.test.fold3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test query set. </p>

Dataset irds.istella22.test.fold3

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test query set. </p>

Dataset irds.istella22.test.fold4.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test query set. </p>

Dataset irds.istella22.test.fold4.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test query set. </p>

Dataset irds.istella22.test.fold4

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test query set. </p>

Dataset irds.istella22.test.fold5.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test query set. </p>

Dataset irds.istella22.test.fold5.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test query set. </p>

Dataset irds.istella22.test.fold5

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test query set. </p>

KILT

<p> KILT is a corpus used for various “knowledge intensive language tasks”. </p> <ul> <li>Documents: Wikipedia articles</li> <li><a href=”https://github.com/facebookresearch/KILT”>Repository</a></li> <li><a href=”https://arxiv.org/abs/2009.02252”>Paper</a></li> <li><a href=”https://ai.facebook.com/tools/kilt/”>Leaderboard</a></li> </ul>

Dataset irds.kilt.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> KILT is a corpus used for various “knowledge intensive language tasks”. </p> <ul> <li>Documents: Wikipedia articles</li> <li><a href=”https://github.com/facebookresearch/KILT”>Repository</a></li> <li><a href=”https://arxiv.org/abs/2009.02252”>Paper</a></li> <li><a href=”https://ai.facebook.com/tools/kilt/”>Leaderboard</a></li> </ul>

Dataset irds.kilt.codec.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> CODEC Entity Ranking sub-task. </p> <ul> <li><a href=”https://github.com/grill-lab/CODEC”>Task Repository</a></li> <li>See also: <a class=”ds-ref”>codec</a>, the document ranking subtask</li> </ul>

Dataset irds.kilt.codec.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> CODEC Entity Ranking sub-task. </p> <ul> <li><a href=”https://github.com/grill-lab/CODEC”>Task Repository</a></li> <li>See also: <a class=”ds-ref”>codec</a>, the document ranking subtask</li> </ul>

Dataset irds.kilt.codec

→ datamaestro_text.datasets.irds.data.Adhoc

<p> CODEC Entity Ranking sub-task. </p> <ul> <li><a href=”https://github.com/grill-lab/CODEC”>Task Repository</a></li> <li>See also: <a class=”ds-ref”>codec</a>, the document ranking subtask</li> </ul>

Dataset irds.kilt.codec.economics.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about economics. </p>

Dataset irds.kilt.codec.economics.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about economics. </p>

Dataset irds.kilt.codec.economics

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about economics. </p>

Dataset irds.kilt.codec.history.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about history. </p>

Dataset irds.kilt.codec.history.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about history. </p>

Dataset irds.kilt.codec.history

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about history. </p>

Dataset irds.kilt.codec.politics.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about politics. </p>

Dataset irds.kilt.codec.politics.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about politics. </p>

Dataset irds.kilt.codec.politics

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>codec</a> that only contains topics about politics. </p>

lotte/lifestyle/dev

<p> Answers from lifestyle-focused forums, including bicycles, coffee, crafts, diy, gardening, lifehacks, mechanics, music, outdoors, parenting, pets, sports, and travel. </p>

Dataset irds.lotte.lifestyle.dev.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from lifestyle-focused forums, including bicycles, coffee, crafts, diy, gardening, lifehacks, mechanics, music, outdoors, parenting, pets, sports, and travel. </p>

Dataset irds.lotte.lifestyle.dev.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/lifestyle/dev</a>. </p>

Dataset irds.lotte.lifestyle.dev.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/lifestyle/dev</a>. </p>

Dataset irds.lotte.lifestyle.dev.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/lifestyle/dev</a>. </p>

Dataset irds.lotte.lifestyle.dev.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/lifestyle/dev</a>. </p>

Dataset irds.lotte.lifestyle.dev.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/lifestyle/dev</a>. </p>

Dataset irds.lotte.lifestyle.dev.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/lifestyle/dev</a>. </p>

lotte/lifestyle/test

<p> Queries and answers from lifestyle-focused forums, including bicycles, coffee, crafts, diy, gardening, lifehacks, mechanics, music, outdoors, parenting, pets, sports, and travel. </p>

Dataset irds.lotte.lifestyle.test.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Queries and answers from lifestyle-focused forums, including bicycles, coffee, crafts, diy, gardening, lifehacks, mechanics, music, outdoors, parenting, pets, sports, and travel. </p>

Dataset irds.lotte.lifestyle.test.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/lifestyle/test</a>. </p>

Dataset irds.lotte.lifestyle.test.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/lifestyle/test</a>. </p>

Dataset irds.lotte.lifestyle.test.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/lifestyle/test</a>. </p>

Dataset irds.lotte.lifestyle.test.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/lifestyle/test</a>. </p>

Dataset irds.lotte.lifestyle.test.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/lifestyle/test</a>. </p>

Dataset irds.lotte.lifestyle.test.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/lifestyle/test</a>. </p>

lotte/pooled/dev

<p> Combined version of <a class=”ds-ref”>lotte/lifestyle/dev</a>, <a class=”ds-ref”>lotte/recreation/dev</a>, <a class=”ds-ref”>lotte/science/dev</a>, <a class=”ds-ref”>lotte/technology/dev</a>, and <a class=”ds-ref”>lotte/writing/dev</a>. </p>

Dataset irds.lotte.pooled.dev.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Combined version of <a class=”ds-ref”>lotte/lifestyle/dev</a>, <a class=”ds-ref”>lotte/recreation/dev</a>, <a class=”ds-ref”>lotte/science/dev</a>, <a class=”ds-ref”>lotte/technology/dev</a>, and <a class=”ds-ref”>lotte/writing/dev</a>. </p>

Dataset irds.lotte.pooled.dev.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/pooled/dev</a>. </p>

Dataset irds.lotte.pooled.dev.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/pooled/dev</a>. </p>

Dataset irds.lotte.pooled.dev.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/pooled/dev</a>. </p>

Dataset irds.lotte.pooled.dev.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/pooled/dev</a>. </p>

Dataset irds.lotte.pooled.dev.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/pooled/dev</a>. </p>

Dataset irds.lotte.pooled.dev.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/pooled/dev</a>. </p>

lotte/pooled/test

<p> Combined version of <a class=”ds-ref”>lotte/lifestyle/test</a>, <a class=”ds-ref”>lotte/recreation/test</a>, <a class=”ds-ref”>lotte/science/test</a>, <a class=”ds-ref”>lotte/technology/test</a>, and <a class=”ds-ref”>lotte/writing/test</a>. </p>

Dataset irds.lotte.pooled.test.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Combined version of <a class=”ds-ref”>lotte/lifestyle/test</a>, <a class=”ds-ref”>lotte/recreation/test</a>, <a class=”ds-ref”>lotte/science/test</a>, <a class=”ds-ref”>lotte/technology/test</a>, and <a class=”ds-ref”>lotte/writing/test</a>. </p>

Dataset irds.lotte.pooled.test.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/pooled/test</a>. </p>

Dataset irds.lotte.pooled.test.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/pooled/test</a>. </p>

Dataset irds.lotte.pooled.test.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/pooled/test</a>. </p>

Dataset irds.lotte.pooled.test.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/pooled/test</a>. </p>

Dataset irds.lotte.pooled.test.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/pooled/test</a>. </p>

Dataset irds.lotte.pooled.test.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/pooled/test</a>. </p>

lotte/recreation/dev

<p> Answers from recreation-focused forums, including anime, boardgames, gaming, movies, photo, rpg, and scifi. </p>

Dataset irds.lotte.recreation.dev.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from recreation-focused forums, including anime, boardgames, gaming, movies, photo, rpg, and scifi. </p>

Dataset irds.lotte.recreation.dev.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/recreation/dev</a>. </p>

Dataset irds.lotte.recreation.dev.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/recreation/dev</a>. </p>

Dataset irds.lotte.recreation.dev.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/recreation/dev</a>. </p>

Dataset irds.lotte.recreation.dev.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/recreation/dev</a>. </p>

Dataset irds.lotte.recreation.dev.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/recreation/dev</a>. </p>

Dataset irds.lotte.recreation.dev.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/recreation/dev</a>. </p>

lotte/recreation/test

<p> Answers from recreation-focused forums, including anime, boardgames, gaming, movies, photo, rpg, and scifi. </p>

Dataset irds.lotte.recreation.test.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from recreation-focused forums, including anime, boardgames, gaming, movies, photo, rpg, and scifi. </p>

Dataset irds.lotte.recreation.test.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/recreation/test</a>. </p>

Dataset irds.lotte.recreation.test.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/recreation/test</a>. </p>

Dataset irds.lotte.recreation.test.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/recreation/test</a>. </p>

Dataset irds.lotte.recreation.test.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/recreation/test</a>. </p>

Dataset irds.lotte.recreation.test.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/recreation/test</a>. </p>

Dataset irds.lotte.recreation.test.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/recreation/test</a>. </p>

lotte/science/dev

<p> Answers from science-focused forums, including academia, astronomy, biology, chemistry, datasciene, earthscience, engineering, math, philosophy, physics, and stats. </p>

Dataset irds.lotte.science.dev.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from science-focused forums, including academia, astronomy, biology, chemistry, datasciene, earthscience, engineering, math, philosophy, physics, and stats. </p>

Dataset irds.lotte.science.dev.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/science/dev</a>. </p>

Dataset irds.lotte.science.dev.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/science/dev</a>. </p>

Dataset irds.lotte.science.dev.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/science/dev</a>. </p>

Dataset irds.lotte.science.dev.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/science/dev</a>. </p>

Dataset irds.lotte.science.dev.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/science/dev</a>. </p>

Dataset irds.lotte.science.dev.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/science/dev</a>. </p>

lotte/science/test

<p> Answers from science-focused forums, including academia, astronomy, biology, chemistry, datasciene, earthscience, engineering, math, philosophy, physics, and stats. </p>

Dataset irds.lotte.science.test.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from science-focused forums, including academia, astronomy, biology, chemistry, datasciene, earthscience, engineering, math, philosophy, physics, and stats. </p>

Dataset irds.lotte.science.test.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/science/test</a>. </p>

Dataset irds.lotte.science.test.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/science/test</a>. </p>

Dataset irds.lotte.science.test.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/science/test</a>. </p>

Dataset irds.lotte.science.test.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/science/test</a>. </p>

Dataset irds.lotte.science.test.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/science/test</a>. </p>

Dataset irds.lotte.science.test.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/science/test</a>. </p>

lotte/technology/dev

<p> Answers from technology-focused forums, including android, apple, askubuntu, electronics, networkengineering, security, serverfault, softwareengineering, superuser, unix, and webapps. </p>

Dataset irds.lotte.technology.dev.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from technology-focused forums, including android, apple, askubuntu, electronics, networkengineering, security, serverfault, softwareengineering, superuser, unix, and webapps. </p>

Dataset irds.lotte.technology.dev.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/technology/dev</a>. </p>

Dataset irds.lotte.technology.dev.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/technology/dev</a>. </p>

Dataset irds.lotte.technology.dev.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/technology/dev</a>. </p>

Dataset irds.lotte.technology.dev.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/technology/dev</a>. </p>

Dataset irds.lotte.technology.dev.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/technology/dev</a>. </p>

Dataset irds.lotte.technology.dev.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/technology/dev</a>. </p>

lotte/technology/test

<p> Answers from technology-focused forums, including android, apple, askubuntu, electronics, networkengineering, security, serverfault, softwareengineering, superuser, unix, and webapps. </p>

Dataset irds.lotte.technology.test.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from technology-focused forums, including android, apple, askubuntu, electronics, networkengineering, security, serverfault, softwareengineering, superuser, unix, and webapps. </p>

Dataset irds.lotte.technology.test.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/technology/test</a>. </p>

Dataset irds.lotte.technology.test.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/technology/test</a>. </p>

Dataset irds.lotte.technology.test.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/technology/test</a>. </p>

Dataset irds.lotte.technology.test.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/technology/test</a>. </p>

Dataset irds.lotte.technology.test.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/technology/test</a>. </p>

Dataset irds.lotte.technology.test.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/technology/test</a>. </p>

lotte/writing/dev

<p> Answers from writing-focused forums, including ell, english, linguistics, literature, worldbuilding, and writing. </p>

Dataset irds.lotte.writing.dev.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from writing-focused forums, including ell, english, linguistics, literature, worldbuilding, and writing. </p>

Dataset irds.lotte.writing.dev.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/writing/dev</a>. </p>

Dataset irds.lotte.writing.dev.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/writing/dev</a>. </p>

Dataset irds.lotte.writing.dev.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/writing/dev</a>. </p>

Dataset irds.lotte.writing.dev.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/writing/dev</a>. </p>

Dataset irds.lotte.writing.dev.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/writing/dev</a>. </p>

Dataset irds.lotte.writing.dev.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/writing/dev</a>. </p>

lotte/writing/test

<p> Answers from writing-focused forums, including ell, english, linguistics, literature, worldbuilding, and writing. </p>

Dataset irds.lotte.writing.test.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Answers from writing-focused forums, including ell, english, linguistics, literature, worldbuilding, and writing. </p>

Dataset irds.lotte.writing.test.forum.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Forum queries for <a class=”ds-ref”>lotte/writing/test</a>. </p>

Dataset irds.lotte.writing.test.forum.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Forum queries for <a class=”ds-ref”>lotte/writing/test</a>. </p>

Dataset irds.lotte.writing.test.forum

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Forum queries for <a class=”ds-ref”>lotte/writing/test</a>. </p>

Dataset irds.lotte.writing.test.search.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Search queries for <a class=”ds-ref”>lotte/writing/test</a>. </p>

Dataset irds.lotte.writing.test.search.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Search queries for <a class=”ds-ref”>lotte/writing/test</a>. </p>

Dataset irds.lotte.writing.test.search

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Search queries for <a class=”ds-ref”>lotte/writing/test</a>. </p>

miracl/ar

<p> The Arabic corpus. </p>

Dataset irds.miracl.ar.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Arabic corpus. </p>

Dataset irds.miracl.ar.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Arabic. </p>

Dataset irds.miracl.ar.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Arabic. </p>

Dataset irds.miracl.ar.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Arabic. </p>

Dataset irds.miracl.ar.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Arabic. </p>

Dataset irds.miracl.ar.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Arabic. </p>

Dataset irds.miracl.ar.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Arabic. </p>

Dataset irds.miracl.ar.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Arabic. </p>

Dataset irds.miracl.ar.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Arabic. </p>

miracl/bn

<p> The Bengali corpus. </p>

Dataset irds.miracl.bn.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Bengali corpus. </p>

Dataset irds.miracl.bn.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Bengali. </p>

Dataset irds.miracl.bn.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Bengali. </p>

Dataset irds.miracl.bn.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Bengali. </p>

Dataset irds.miracl.bn.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Bengali. </p>

Dataset irds.miracl.bn.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Bengali. </p>

Dataset irds.miracl.bn.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Bengali. </p>

Dataset irds.miracl.bn.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Bengali. </p>

Dataset irds.miracl.bn.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Bengali. </p>

miracl/de

<p> The German corpus. </p>

Dataset irds.miracl.de.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The German corpus. </p>

Dataset irds.miracl.de.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for German. </p>

Dataset irds.miracl.de.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for German. </p>

Dataset irds.miracl.de.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for German. </p>

Dataset irds.miracl.de.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for German. </p>

miracl/en

<p> The English corpus. </p>

Dataset irds.miracl.en.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The English corpus. </p>

Dataset irds.miracl.en.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for English. </p>

Dataset irds.miracl.en.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for English. </p>

Dataset irds.miracl.en.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for English. </p>

Dataset irds.miracl.en.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for English. </p>

Dataset irds.miracl.en.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for English. </p>

Dataset irds.miracl.en.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for English. </p>

Dataset irds.miracl.en.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for English. </p>

Dataset irds.miracl.en.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for English. </p>

miracl/es

<p> The Spanish corpus. </p>

Dataset irds.miracl.es.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Spanish corpus. </p>

Dataset irds.miracl.es.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Spanish. </p>

Dataset irds.miracl.es.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Spanish. </p>

Dataset irds.miracl.es.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Spanish. </p>

Dataset irds.miracl.es.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Spanish. </p>

Dataset irds.miracl.es.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Spanish. </p>

Dataset irds.miracl.es.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Spanish. </p>

Dataset irds.miracl.es.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Spanish. </p>

miracl/fa

<p> The Persian corpus. </p>

Dataset irds.miracl.fa.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Persian corpus. </p>

Dataset irds.miracl.fa.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Persian. </p>

Dataset irds.miracl.fa.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Persian. </p>

Dataset irds.miracl.fa.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Persian. </p>

Dataset irds.miracl.fa.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Persian. </p>

Dataset irds.miracl.fa.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Persian. </p>

Dataset irds.miracl.fa.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Persian. </p>

Dataset irds.miracl.fa.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Persian. </p>

miracl/fi

<p> The Finnish corpus. </p>

Dataset irds.miracl.fi.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Finnish corpus. </p>

Dataset irds.miracl.fi.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Finnish. </p>

Dataset irds.miracl.fi.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Finnish. </p>

Dataset irds.miracl.fi.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Finnish. </p>

Dataset irds.miracl.fi.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Finnish. </p>

Dataset irds.miracl.fi.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Finnish. </p>

Dataset irds.miracl.fi.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Finnish. </p>

Dataset irds.miracl.fi.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Finnish. </p>

Dataset irds.miracl.fi.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Finnish. </p>

miracl/fr

<p> The French corpus. </p>

Dataset irds.miracl.fr.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The French corpus. </p>

Dataset irds.miracl.fr.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for French. </p>

Dataset irds.miracl.fr.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for French. </p>

Dataset irds.miracl.fr.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for French. </p>

Dataset irds.miracl.fr.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for French. </p>

Dataset irds.miracl.fr.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for French. </p>

Dataset irds.miracl.fr.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for French. </p>

Dataset irds.miracl.fr.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for French. </p>

miracl/hi

<p> The Hindi corpus. </p>

Dataset irds.miracl.hi.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Hindi corpus. </p>

Dataset irds.miracl.hi.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Hindi. </p>

Dataset irds.miracl.hi.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Hindi. </p>

Dataset irds.miracl.hi.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Hindi. </p>

Dataset irds.miracl.hi.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Hindi. </p>

Dataset irds.miracl.hi.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Hindi. </p>

Dataset irds.miracl.hi.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Hindi. </p>

Dataset irds.miracl.hi.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Hindi. </p>

miracl/id

<p> The Indonesian corpus. </p>

Dataset irds.miracl.id.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Indonesian corpus. </p>

Dataset irds.miracl.id.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Indonesian. </p>

Dataset irds.miracl.id.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Indonesian. </p>

Dataset irds.miracl.id.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Indonesian. </p>

Dataset irds.miracl.id.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Indonesian. </p>

Dataset irds.miracl.id.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Indonesian. </p>

Dataset irds.miracl.id.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Indonesian. </p>

Dataset irds.miracl.id.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Indonesian. </p>

Dataset irds.miracl.id.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Indonesian. </p>

miracl/ja

<p> The Japanese corpus. </p>

Dataset irds.miracl.ja.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Japanese corpus. </p>

Dataset irds.miracl.ja.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Japanese. </p>

Dataset irds.miracl.ja.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Japanese. </p>

Dataset irds.miracl.ja.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Japanese. </p>

Dataset irds.miracl.ja.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Japanese. </p>

Dataset irds.miracl.ja.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Japanese. </p>

Dataset irds.miracl.ja.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Japanese. </p>

Dataset irds.miracl.ja.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Japanese. </p>

Dataset irds.miracl.ja.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Japanese. </p>

miracl/ko

<p> The Korean corpus. </p>

Dataset irds.miracl.ko.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Korean corpus. </p>

Dataset irds.miracl.ko.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Korean. </p>

Dataset irds.miracl.ko.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Korean. </p>

Dataset irds.miracl.ko.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Korean. </p>

Dataset irds.miracl.ko.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Korean. </p>

Dataset irds.miracl.ko.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Korean. </p>

Dataset irds.miracl.ko.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Korean. </p>

Dataset irds.miracl.ko.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Korean. </p>

Dataset irds.miracl.ko.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Korean. </p>

miracl/ru

<p> The Russian corpus. </p>

Dataset irds.miracl.ru.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Russian corpus. </p>

Dataset irds.miracl.ru.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Russian. </p>

Dataset irds.miracl.ru.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Russian. </p>

Dataset irds.miracl.ru.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Russian. </p>

Dataset irds.miracl.ru.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Russian. </p>

Dataset irds.miracl.ru.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Russian. </p>

Dataset irds.miracl.ru.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Russian. </p>

Dataset irds.miracl.ru.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Russian. </p>

Dataset irds.miracl.ru.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Russian. </p>

miracl/sw

<p> The Swahili corpus. </p>

Dataset irds.miracl.sw.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Swahili corpus. </p>

Dataset irds.miracl.sw.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Swahili. </p>

Dataset irds.miracl.sw.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Swahili. </p>

Dataset irds.miracl.sw.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Swahili. </p>

Dataset irds.miracl.sw.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Swahili. </p>

Dataset irds.miracl.sw.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Swahili. </p>

Dataset irds.miracl.sw.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Swahili. </p>

Dataset irds.miracl.sw.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Swahili. </p>

Dataset irds.miracl.sw.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Swahili. </p>

miracl/te

<p> The Telugu corpus. </p>

Dataset irds.miracl.te.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Telugu corpus. </p>

Dataset irds.miracl.te.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Telugu. </p>

Dataset irds.miracl.te.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Telugu. </p>

Dataset irds.miracl.te.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Telugu. </p>

Dataset irds.miracl.te.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Telugu. </p>

Dataset irds.miracl.te.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Telugu. </p>

Dataset irds.miracl.te.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Telugu. </p>

Dataset irds.miracl.te.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Telugu. </p>

Dataset irds.miracl.te.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Telugu. </p>

miracl/th

<p> The Thai corpus. </p>

Dataset irds.miracl.th.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Thai corpus. </p>

Dataset irds.miracl.th.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Thai. </p>

Dataset irds.miracl.th.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Thai. </p>

Dataset irds.miracl.th.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Thai. </p>

Dataset irds.miracl.th.test-a.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version a) for Thai. </p>

Dataset irds.miracl.th.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Thai. </p>

Dataset irds.miracl.th.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Thai. </p>

Dataset irds.miracl.th.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Thai. </p>

Dataset irds.miracl.th.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Thai. </p>

miracl/yo

<p> The Yoruba corpus. </p>

Dataset irds.miracl.yo.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Yoruba corpus. </p>

Dataset irds.miracl.yo.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Yoruba. </p>

Dataset irds.miracl.yo.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Yoruba. </p>

Dataset irds.miracl.yo.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Yoruba. </p>

Dataset irds.miracl.yo.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Yoruba. </p>

miracl/zh

<p> The Chinese corpus. </p>

Dataset irds.miracl.zh.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Chinese corpus. </p>

Dataset irds.miracl.zh.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The dev set for Chinese. </p>

Dataset irds.miracl.zh.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The dev set for Chinese. </p>

Dataset irds.miracl.zh.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The dev set for Chinese. </p>

Dataset irds.miracl.zh.test-b.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The held-out test set (version b) for Chinese. </p>

Dataset irds.miracl.zh.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The train set for Chinese. </p>

Dataset irds.miracl.zh.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The train set for Chinese. </p>

Dataset irds.miracl.zh.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The train set for Chinese. </p>

MSMARCO (passage)

<p> A passage ranking benchmark with a collection of 8.8 million passages and question queries. Most relevance judgments are shallow (typically at most 1-2 per query), but the TREC Deep Learning track adds deep judgments. Evaluation typically conducted using MRR@10. </p> <p> Note that the original document source files for this collection contain a double-encoding error that cause strange sequences like “嬔 and “ðºð”. These are automatically corrrected (properly converting previous examples to “公” and “🇺🇸”). </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-document</a></li> <li>Documents: Short passages (from web)</li> <li>Queries: Natural language questions (from query log)</li> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-passage.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A passage ranking benchmark with a collection of 8.8 million passages and question queries. Most relevance judgments are shallow (typically at most 1-2 per query), but the TREC Deep Learning track adds deep judgments. Evaluation typically conducted using MRR@10. </p> <p> Note that the original document source files for this collection contain a double-encoding error that cause strange sequences like “嬔 and “ðºð”. These are automatically corrrected (properly converting previous examples to “公” and “🇺🇸”). </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-document</a></li> <li>Documents: Short passages (from web)</li> <li>Queries: Natural language questions (from query log)</li> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-passage.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev set. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available dev queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p>

Dataset irds.msmarco-passage.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev set. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available dev queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p>

Dataset irds.msmarco-passage.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev set. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available dev queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p>

Dataset irds.msmarco-passage.dev.2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> “Dev2” split of the <a class=”ds-ref”>msmarco-passage/dev</a> set. Originally released as part of the v2 corpus. </p>

Dataset irds.msmarco-passage.dev.2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> “Dev2” split of the <a class=”ds-ref”>msmarco-passage/dev</a> set. Originally released as part of the v2 corpus. </p>

Dataset irds.msmarco-passage.dev.2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> “Dev2” split of the <a class=”ds-ref”>msmarco-passage/dev</a> set. Originally released as part of the v2 corpus. </p>

Dataset irds.msmarco-passage.dev.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-passage/dev</a> that only includes queries that have at least one qrel. </p>

Dataset irds.msmarco-passage.dev.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-passage/dev</a> that only includes queries that have at least one qrel. </p>

Dataset irds.msmarco-passage.dev.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-passage/dev</a> that only includes queries that have at least one qrel. </p>

Dataset irds.msmarco-passage.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official “small” version of the dev set, consisting of 6,980 queries (6.9% of the full dev set). </p>

Dataset irds.msmarco-passage.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official “small” version of the dev set, consisting of 6,980 queries (6.9% of the full dev set). </p>

Dataset irds.msmarco-passage.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official “small” version of the dev set, consisting of 6,980 queries (6.9% of the full dev set). </p>

Dataset irds.msmarco-passage.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official “small” version of the dev set, consisting of 6,980 queries (6.9% of the full dev set). </p>

Dataset irds.msmarco-passage.eval.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official eval set for submission to MS MARCO leaderboard. Relevance judgments are hidden. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available eval queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p>

Dataset irds.msmarco-passage.eval.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official “small” version of the eval set, consisting of 6,837 queries (6.8% of the full eval set). </p>

Dataset irds.msmarco-passage.eval.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official “small” version of the eval set, consisting of 6,837 queries (6.8% of the full eval set). </p>

Dataset irds.msmarco-passage.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set. </p> <p> Not all queries have relevance judgments. Use <a class=”ds-ref”>msmarco-passage/train/judged</a> for a filtered list that only includes documents that have at least one qrel. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available train queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p> <p> docpairs provides access to the “official” sequence for pairwise training. </p>

Dataset irds.msmarco-passage.train.docpairs

<p> Official train set. </p> <p> Not all queries have relevance judgments. Use <a class=”ds-ref”>msmarco-passage/train/judged</a> for a filtered list that only includes documents that have at least one qrel. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available train queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p> <p> docpairs provides access to the “official” sequence for pairwise training. </p>

Dataset irds.msmarco-passage.train.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official train set. </p> <p> Not all queries have relevance judgments. Use <a class=”ds-ref”>msmarco-passage/train/judged</a> for a filtered list that only includes documents that have at least one qrel. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available train queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p> <p> docpairs provides access to the “official” sequence for pairwise training. </p>

Dataset irds.msmarco-passage.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set. </p> <p> Not all queries have relevance judgments. Use <a class=”ds-ref”>msmarco-passage/train/judged</a> for a filtered list that only includes documents that have at least one qrel. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available train queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p> <p> docpairs provides access to the “official” sequence for pairwise training. </p>

Dataset irds.msmarco-passage.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set. </p> <p> Not all queries have relevance judgments. Use <a class=”ds-ref”>msmarco-passage/train/judged</a> for a filtered list that only includes documents that have at least one qrel. </p> <p> scoreddocs are the top 1000 results from BM25. These are used for the “re-ranking” setting. Note that these are sub-sampled to about 1/8 of the total available train queries by the MSMARCO authors for faster evaluation. The BM25 scores from scoreddocs are not available (all have a score of 0). </p> <p> docpairs provides access to the “official” sequence for pairwise training. </p>

Dataset irds.msmarco-passage.train.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have at least one qrel. </p>

Dataset irds.msmarco-passage.train.judged.docpairs

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have at least one qrel. </p>

Dataset irds.msmarco-passage.train.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have at least one qrel. </p>

Dataset irds.msmarco-passage.train.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have at least one qrel. </p>

Dataset irds.msmarco-passage.train.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have at least one qrel. </p>

Dataset irds.msmarco-passage.train.medical.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have a layman or expert medical term. Note that this includes about 20% false matches due to terms with multiple senses. </p>

Dataset irds.msmarco-passage.train.medical.docpairs

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have a layman or expert medical term. Note that this includes about 20% false matches due to terms with multiple senses. </p>

Dataset irds.msmarco-passage.train.medical.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have a layman or expert medical term. Note that this includes about 20% false matches due to terms with multiple senses. </p>

Dataset irds.msmarco-passage.train.medical.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have a layman or expert medical term. Note that this includes about 20% false matches due to terms with multiple senses. </p>

Dataset irds.msmarco-passage.train.medical

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> that only includes queries that have a layman or expert medical term. Note that this includes about 20% false matches due to terms with multiple senses. </p>

Dataset irds.msmarco-passage.train.split200-train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> without 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-train.docpairs

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> without 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-train.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> without 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> without 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> without 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-valid.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> with only 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-valid.docpairs

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> with only 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-valid.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> with only 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-valid.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> with only 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.split200-valid

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-passage/train</a> with only 200 queries that are meant to be used as a small validation set. From various works. </p>

Dataset irds.msmarco-passage.train.triples-small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with the “small” triples file (a 10% sample of the full file). </p> <p> Note that to save on storage space (27GB), the contents of the file are mapped to their corresponding query and document IDs. This process takes a few minutes to run the first time the triples are requested. </p>

Dataset irds.msmarco-passage.train.triples-small.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with the “small” triples file (a 10% sample of the full file). </p> <p> Note that to save on storage space (27GB), the contents of the file are mapped to their corresponding query and document IDs. This process takes a few minutes to run the first time the triples are requested. </p>

Dataset irds.msmarco-passage.train.triples-small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with the “small” triples file (a 10% sample of the full file). </p> <p> Note that to save on storage space (27GB), the contents of the file are mapped to their corresponding query and document IDs. This process takes a few minutes to run the first time the triples are requested. </p>

Dataset irds.msmarco-passage.train.triples-small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with the “small” triples file (a 10% sample of the full file). </p> <p> Note that to save on storage space (27GB), the contents of the file are mapped to their corresponding query and document IDs. This process takes a few minutes to run the first time the triples are requested. </p>

Dataset irds.msmarco-passage.train.triples-small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with the “small” triples file (a 10% sample of the full file). </p> <p> Note that to save on storage space (27GB), the contents of the file are mapped to their corresponding query and document IDs. This process takes a few minutes to run the first time the triples are requested. </p>

Dataset irds.msmarco-passage.train.triples-v2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with version 2 of the triples file. </p> <p> This version of the triples file includes rows that were accidently missing from version 1 of the file (see discussion <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/commit/4695a71c6c76ce85c07a51c0f12690cab19abbb0”>here</a>). </p> <p> Note that this is sorted by the IDs in the file, so you probably would not want to use it unless you first shuffle it before usage. <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/issues/21”>We opened an issue</a> suggesting that a third version of the file is provided that is shuffled so that the order is consistent across groups using the data, but at this time, no such file exists in an official capacity. </p>

Dataset irds.msmarco-passage.train.triples-v2.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with version 2 of the triples file. </p> <p> This version of the triples file includes rows that were accidently missing from version 1 of the file (see discussion <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/commit/4695a71c6c76ce85c07a51c0f12690cab19abbb0”>here</a>). </p> <p> Note that this is sorted by the IDs in the file, so you probably would not want to use it unless you first shuffle it before usage. <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/issues/21”>We opened an issue</a> suggesting that a third version of the file is provided that is shuffled so that the order is consistent across groups using the data, but at this time, no such file exists in an official capacity. </p>

Dataset irds.msmarco-passage.train.triples-v2.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with version 2 of the triples file. </p> <p> This version of the triples file includes rows that were accidently missing from version 1 of the file (see discussion <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/commit/4695a71c6c76ce85c07a51c0f12690cab19abbb0”>here</a>). </p> <p> Note that this is sorted by the IDs in the file, so you probably would not want to use it unless you first shuffle it before usage. <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/issues/21”>We opened an issue</a> suggesting that a third version of the file is provided that is shuffled so that the order is consistent across groups using the data, but at this time, no such file exists in an official capacity. </p>

Dataset irds.msmarco-passage.train.triples-v2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with version 2 of the triples file. </p> <p> This version of the triples file includes rows that were accidently missing from version 1 of the file (see discussion <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/commit/4695a71c6c76ce85c07a51c0f12690cab19abbb0”>here</a>). </p> <p> Note that this is sorted by the IDs in the file, so you probably would not want to use it unless you first shuffle it before usage. <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/issues/21”>We opened an issue</a> suggesting that a third version of the file is provided that is shuffled so that the order is consistent across groups using the data, but at this time, no such file exists in an official capacity. </p>

Dataset irds.msmarco-passage.train.triples-v2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, but with version 2 of the triples file. </p> <p> This version of the triples file includes rows that were accidently missing from version 1 of the file (see discussion <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/commit/4695a71c6c76ce85c07a51c0f12690cab19abbb0”>here</a>). </p> <p> Note that this is sorted by the IDs in the file, so you probably would not want to use it unless you first shuffle it before usage. <a href=”https://github.com/microsoft/MSMARCO-Passage-Ranking/issues/21”>We opened an issue</a> suggesting that a third version of the file is provided that is shuffled so that the order is consistent across groups using the data, but at this time, no such file exists in an official capacity. </p>

Dataset irds.msmarco-passage.trec-dl-2019.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-passage/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-passage/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-2019.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-passage/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-passage/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-2019.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-passage/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-passage/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-2019

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-passage/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-passage/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-2019.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-passage.trec-dl-2019.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-passage.trec-dl-2019.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-passage.trec-dl-2019.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-passage.trec-dl-2020.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-passage/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-passage/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-2020.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-passage/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-passage/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-2020.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-passage/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-passage/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-2020

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-passage/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-passage/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-2020.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-passage.trec-dl-2020.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-passage.trec-dl-2020.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-passage.trec-dl-2020.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-passage.trec-dl-hard.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A more challenging subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a> and <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>. </p> <ul> <li><a href=”https://github.com/grill-lab/DL-Hard”>data website</a></li> <li>See Also: <a class=”ds-ref”>msmarco-document/trec-dl-hard</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-hard.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A more challenging subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a> and <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>. </p> <ul> <li><a href=”https://github.com/grill-lab/DL-Hard”>data website</a></li> <li>See Also: <a class=”ds-ref”>msmarco-document/trec-dl-hard</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-hard

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A more challenging subset of <a class=”ds-ref”>msmarco-passage/trec-dl-2019</a> and <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>. </p> <ul> <li><a href=”https://github.com/grill-lab/DL-Hard”>data website</a></li> <li>See Also: <a class=”ds-ref”>msmarco-document/trec-dl-hard</a></li> </ul>

Dataset irds.msmarco-passage.trec-dl-hard.fold1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 1 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 1 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 1 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 2 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 2 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 2 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 3 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 3 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold3

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 3 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold4.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 4 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold4.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 4 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold4

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 4 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold5.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 5 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold5.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 5 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

Dataset irds.msmarco-passage.trec-dl-hard.fold5

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 5 of <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a> </p>

mmarco/de

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into German. </p>

Dataset irds.mmarco.de.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into German. </p>

Dataset irds.mmarco.de.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.de.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into German. </p>

mmarco/es

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Spanish. </p>

Dataset irds.mmarco.es.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Spanish. </p>

Dataset irds.mmarco.es.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.es.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Spanish. </p>

mmarco/fr

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into French. </p>

Dataset irds.mmarco.fr.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into French. </p>

Dataset irds.mmarco.fr.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.fr.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into French. </p>

mmarco/id

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Indonesian. </p>

Dataset irds.mmarco.id.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Indonesian. </p>

Dataset irds.mmarco.id.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.id.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Indonesian. </p>

mmarco/it

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Italian. </p>

Dataset irds.mmarco.it.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Italian. </p>

Dataset irds.mmarco.it.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.it.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Italian. </p>

mmarco/pt

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.dev.small.v1.1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.dev.small.v1.1.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.dev.small.v1.1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.dev.small.v1.1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.dev.v1.1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.dev.v1.1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.dev.v1.1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.pt.train.v1.1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.train.v1.1.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.train.v1.1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

Dataset irds.mmarco.pt.train.v1.1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. It also removes some duplicated query IDs. </p>

mmarco/ru

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Russian. </p>

Dataset irds.mmarco.ru.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Russian. </p>

Dataset irds.mmarco.ru.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.ru.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Russian. </p>

mmarco/v2/ar

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Arabic. </p>

Dataset irds.mmarco.v2.ar.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Arabic. </p>

mmarco/v2/de

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into German. </p>

Dataset irds.mmarco.v2.de.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into German. </p>

mmarco/v2/dt

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Dutch. </p>

Dataset irds.mmarco.v2.dt.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Dutch. </p>

mmarco/v2/es

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Spanish. </p>

Dataset irds.mmarco.v2.es.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Spanish. </p>

mmarco/v2/fr

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into French. </p>

Dataset irds.mmarco.v2.fr.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into French. </p>

mmarco/v2/hi

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Hindi. </p>

Dataset irds.mmarco.v2.hi.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Hindi. </p>

mmarco/v2/id

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Indonesian. </p>

Dataset irds.mmarco.v2.id.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Indonesian. </p>

mmarco/v2/it

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Italian. </p>

Dataset irds.mmarco.v2.it.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Italian. </p>

mmarco/v2/ja

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Japanese. </p>

Dataset irds.mmarco.v2.ja.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Japanese. </p>

mmarco/v2/pt

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p>

Dataset irds.mmarco.v2.pt.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Portuguese. </p>

mmarco/v2/ru

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Russian. </p>

Dataset irds.mmarco.v2.ru.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Russian. </p>

mmarco/v2/vi

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Vietnamese. </p>

Dataset irds.mmarco.v2.vi.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Vietnamese. </p>

mmarco/v2/zh

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.dev.small.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.v2.zh.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Chinese. </p>

mmarco/zh

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Chinese. </p>

Dataset irds.mmarco.zh.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version of <a class=”ds-ref”>msmarco-passage</a>, with documents translated into Chinese. </p>

Dataset irds.mmarco.zh.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.dev.small.v1.1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. </p>

Dataset irds.mmarco.zh.dev.small.v1.1.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. </p>

Dataset irds.mmarco.zh.dev.small.v1.1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. </p>

Dataset irds.mmarco.zh.dev.small.v1.1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. </p>

Dataset irds.mmarco.zh.dev.v1.1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. </p>

Dataset irds.mmarco.zh.dev.v1.1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. </p>

Dataset irds.mmarco.zh.dev.v1.1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/dev</a>, with queries and documents translated into Chinese. </p> <p> Version 1.1 of this file includes manual corrections from the authorss of the translated files. <a href=”https://github.com/unicamp-dl/mMARCO/issues/8#issuecomment-992810293”>See discussion here</a>. </p>

Dataset irds.mmarco.zh.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.train.docpairs

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Chinese. </p>

Dataset irds.mmarco.zh.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Version of <a class=”ds-ref”>msmarco-passage/train</a>, with queries and documents translated into Chinese. </p>

mr-tydi/ar

<p> Complete Arabic dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ar.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Arabic dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ar.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Arabic dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ar.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Arabic dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ar

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Arabic dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ar.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Arabic</p>

Dataset irds.mr-tydi.ar.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Arabic</p>

Dataset irds.mr-tydi.ar.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Arabic</p>

Dataset irds.mr-tydi.ar.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Arabic</p>

Dataset irds.mr-tydi.ar.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Arabic</p>

Dataset irds.mr-tydi.ar.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Arabic</p>

Dataset irds.mr-tydi.ar.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Arabic</p>

Dataset irds.mr-tydi.ar.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Arabic</p>

Dataset irds.mr-tydi.ar.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Arabic</p>

mr-tydi/bn

<p> Complete Bengali dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.bn.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Bengali dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.bn.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Bengali dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.bn.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Bengali dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.bn

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Bengali dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.bn.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Bengali</p>

Dataset irds.mr-tydi.bn.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Bengali</p>

Dataset irds.mr-tydi.bn.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Bengali</p>

Dataset irds.mr-tydi.bn.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Bengali</p>

Dataset irds.mr-tydi.bn.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Bengali</p>

Dataset irds.mr-tydi.bn.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Bengali</p>

Dataset irds.mr-tydi.bn.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Bengali</p>

Dataset irds.mr-tydi.bn.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Bengali</p>

Dataset irds.mr-tydi.bn.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Bengali</p>

mr-tydi/en

<p> Complete English dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.en.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete English dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.en.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete English dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.en.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete English dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.en

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete English dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.en.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for English</p>

Dataset irds.mr-tydi.en.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for English</p>

Dataset irds.mr-tydi.en.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for English</p>

Dataset irds.mr-tydi.en.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for English</p>

Dataset irds.mr-tydi.en.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for English</p>

Dataset irds.mr-tydi.en.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for English</p>

Dataset irds.mr-tydi.en.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for English</p>

Dataset irds.mr-tydi.en.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for English</p>

Dataset irds.mr-tydi.en.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for English</p>

mr-tydi/fi

<p> Complete Finnish dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.fi.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Finnish dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.fi.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Finnish dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.fi.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Finnish dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.fi

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Finnish dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.fi.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Finnish</p>

Dataset irds.mr-tydi.fi.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Finnish</p>

Dataset irds.mr-tydi.fi.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Finnish</p>

Dataset irds.mr-tydi.fi.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Finnish</p>

Dataset irds.mr-tydi.fi.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Finnish</p>

Dataset irds.mr-tydi.fi.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Finnish</p>

Dataset irds.mr-tydi.fi.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Finnish</p>

Dataset irds.mr-tydi.fi.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Finnish</p>

Dataset irds.mr-tydi.fi.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Finnish</p>

mr-tydi/id

<p> Complete Indonesian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.id.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Indonesian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.id.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Indonesian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.id.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Indonesian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.id

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Indonesian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.id.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Indonesian</p>

Dataset irds.mr-tydi.id.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Indonesian</p>

Dataset irds.mr-tydi.id.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Indonesian</p>

Dataset irds.mr-tydi.id.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Indonesian</p>

Dataset irds.mr-tydi.id.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Indonesian</p>

Dataset irds.mr-tydi.id.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Indonesian</p>

Dataset irds.mr-tydi.id.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Indonesian</p>

Dataset irds.mr-tydi.id.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Indonesian</p>

Dataset irds.mr-tydi.id.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Indonesian</p>

mr-tydi/ja

<p> Complete Japanese dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ja.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Japanese dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ja.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Japanese dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ja.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Japanese dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ja

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Japanese dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ja.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Japanese</p>

Dataset irds.mr-tydi.ja.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Japanese</p>

Dataset irds.mr-tydi.ja.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Japanese</p>

Dataset irds.mr-tydi.ja.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Japanese</p>

Dataset irds.mr-tydi.ja.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Japanese</p>

Dataset irds.mr-tydi.ja.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Japanese</p>

Dataset irds.mr-tydi.ja.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Japanese</p>

Dataset irds.mr-tydi.ja.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Japanese</p>

Dataset irds.mr-tydi.ja.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Japanese</p>

mr-tydi/ko

<p> Complete Korean dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ko.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Korean dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ko.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Korean dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ko.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Korean dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ko

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Korean dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ko.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Korean</p>

Dataset irds.mr-tydi.ko.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Korean</p>

Dataset irds.mr-tydi.ko.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Korean</p>

Dataset irds.mr-tydi.ko.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Korean</p>

Dataset irds.mr-tydi.ko.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Korean</p>

Dataset irds.mr-tydi.ko.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Korean</p>

Dataset irds.mr-tydi.ko.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Korean</p>

Dataset irds.mr-tydi.ko.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Korean</p>

Dataset irds.mr-tydi.ko.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Korean</p>

mr-tydi/ru

<p> Complete Russian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ru.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Russian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ru.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Russian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ru.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Russian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ru

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Russian dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.ru.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Russian</p>

Dataset irds.mr-tydi.ru.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Russian</p>

Dataset irds.mr-tydi.ru.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Russian</p>

Dataset irds.mr-tydi.ru.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Russian</p>

Dataset irds.mr-tydi.ru.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Russian</p>

Dataset irds.mr-tydi.ru.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Russian</p>

Dataset irds.mr-tydi.ru.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Russian</p>

Dataset irds.mr-tydi.ru.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Russian</p>

Dataset irds.mr-tydi.ru.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Russian</p>

mr-tydi/sw

<p> Complete Swahili dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.sw.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Swahili dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.sw.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Swahili dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.sw.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Swahili dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.sw

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Swahili dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.sw.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Swahili</p>

Dataset irds.mr-tydi.sw.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Swahili</p>

Dataset irds.mr-tydi.sw.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Swahili</p>

Dataset irds.mr-tydi.sw.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Swahili</p>

Dataset irds.mr-tydi.sw.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Swahili</p>

Dataset irds.mr-tydi.sw.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Swahili</p>

Dataset irds.mr-tydi.sw.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Swahili</p>

Dataset irds.mr-tydi.sw.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Swahili</p>

Dataset irds.mr-tydi.sw.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Swahili</p>

mr-tydi/te

<p> Complete Telugu dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.te.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Telugu dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.te.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Telugu dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.te.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Telugu dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.te

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Telugu dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.te.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Telugu</p>

Dataset irds.mr-tydi.te.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Telugu</p>

Dataset irds.mr-tydi.te.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Telugu</p>

Dataset irds.mr-tydi.te.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Telugu</p>

Dataset irds.mr-tydi.te.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Telugu</p>

Dataset irds.mr-tydi.te.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Telugu</p>

Dataset irds.mr-tydi.te.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Telugu</p>

Dataset irds.mr-tydi.te.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Telugu</p>

Dataset irds.mr-tydi.te.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Telugu</p>

mr-tydi/th

<p> Complete Thai dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.th.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Complete Thai dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.th.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Complete Thai dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.th.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Complete Thai dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.th

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Complete Thai dataset, including all train, dev, and test queries and qrels. </p>

Dataset irds.mr-tydi.th.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Development set for Thai</p>

Dataset irds.mr-tydi.th.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Development set for Thai</p>

Dataset irds.mr-tydi.th.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Development set for Thai</p>

Dataset irds.mr-tydi.th.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Test set for Thai</p>

Dataset irds.mr-tydi.th.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Test set for Thai</p>

Dataset irds.mr-tydi.th.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Test set for Thai</p>

Dataset irds.mr-tydi.th.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>Train set for Thai</p>

Dataset irds.mr-tydi.th.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>Train set for Thai</p>

Dataset irds.mr-tydi.th.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>Train set for Thai</p>

MSMARCO (document)

<p> “Based the questions in the [MS-MARCO] Question Answering Dataset and the documents which answered the questions a document ranking task was formulated. There are 3.2 million documents and the goal is to rank based on their relevance. Relevance labels are derived from what passages was marked as having the answer in the QnA dataset.” </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> <li>Documents: Text extracted from web pages</li> <li>Queries: Natural language questions (from query log)</li> <li><a href=”https://microsoft.github.io/msmarco/#docranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-document.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> “Based the questions in the [MS-MARCO] Question Answering Dataset and the documents which answered the questions a document ranking task was formulated. There are 3.2 million documents and the goal is to rank based on their relevance. Relevance labels are derived from what passages was marked as having the answer in the QnA dataset.” </p> <ul> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> <li>Documents: Text extracted from web pages</li> <li>Queries: Natural language questions (from query log)</li> <li><a href=”https://microsoft.github.io/msmarco/#docranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-document.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev set. All queries have exactly 1 (positive) relevance judgment. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.dev.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official dev set. All queries have exactly 1 (positive) relevance judgment. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev set. All queries have exactly 1 (positive) relevance judgment. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev set. All queries have exactly 1 (positive) relevance judgment. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.eval.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official eval set for submission to MS MARCO leaderboard. Relevance judgments are hidden. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.eval.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official eval set for submission to MS MARCO leaderboard. Relevance judgments are hidden. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.orcas.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> “ORCAS is a click-based dataset associated with the TREC Deep Learning Track. It covers 1.4 million of the TREC DL documents, providing 18 million connections to 10 million distinct queries.” </p> <ul> <li>Queries: From query log</li> <li>Relevance Data: User clicks</li> <li>Scored docs: Indri Query Likelihood model</li> <li><a href=”https://arxiv.org/abs/2006.05324”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-document.orcas.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> “ORCAS is a click-based dataset associated with the TREC Deep Learning Track. It covers 1.4 million of the TREC DL documents, providing 18 million connections to 10 million distinct queries.” </p> <ul> <li>Queries: From query log</li> <li>Relevance Data: User clicks</li> <li>Scored docs: Indri Query Likelihood model</li> <li><a href=”https://arxiv.org/abs/2006.05324”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-document.orcas.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> “ORCAS is a click-based dataset associated with the TREC Deep Learning Track. It covers 1.4 million of the TREC DL documents, providing 18 million connections to 10 million distinct queries.” </p> <ul> <li>Queries: From query log</li> <li>Relevance Data: User clicks</li> <li>Scored docs: Indri Query Likelihood model</li> <li><a href=”https://arxiv.org/abs/2006.05324”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-document.orcas

→ datamaestro_text.datasets.irds.data.Adhoc

<p> “ORCAS is a click-based dataset associated with the TREC Deep Learning Track. It covers 1.4 million of the TREC DL documents, providing 18 million connections to 10 million distinct queries.” </p> <ul> <li>Queries: From query log</li> <li>Relevance Data: User clicks</li> <li>Scored docs: Indri Query Likelihood model</li> <li><a href=”https://arxiv.org/abs/2006.05324”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-document.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set. All queries have exactly 1 (positive) relevance judgment. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.train.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official train set. All queries have exactly 1 (positive) relevance judgment. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set. All queries have exactly 1 (positive) relevance judgment. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set. All queries have exactly 1 (positive) relevance judgment. </p> <p> scoreddocs are the top 100 results from Indri QL. These are used for the “re-ranking” setting. </p>

Dataset irds.msmarco-document.trec-dl-2019.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-2019.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-2019.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-2019

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-2019.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-document/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document.trec-dl-2019.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Subset of <a class=”ds-ref”>msmarco-document/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document.trec-dl-2019.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-document/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document.trec-dl-2019.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-document/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document.trec-dl-2020.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-2020.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-2020.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-2020

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-2020.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document.trec-dl-2020.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Subset of <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document.trec-dl-2020.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document.trec-dl-2020.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document.trec-dl-hard.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A more challenging subset of <a class=”ds-ref”>msmarco-document/trec-dl-2019</a> and <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>. </p> <ul> <li><a href=”https://github.com/grill-lab/DL-Hard”>data website</a></li> <li>See Also: <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-hard.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A more challenging subset of <a class=”ds-ref”>msmarco-document/trec-dl-2019</a> and <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>. </p> <ul> <li><a href=”https://github.com/grill-lab/DL-Hard”>data website</a></li> <li>See Also: <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-hard

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A more challenging subset of <a class=”ds-ref”>msmarco-document/trec-dl-2019</a> and <a class=”ds-ref”>msmarco-document/trec-dl-2020</a>. </p> <ul> <li><a href=”https://github.com/grill-lab/DL-Hard”>data website</a></li> <li>See Also: <a class=”ds-ref”>msmarco-passage/trec-dl-hard</a></li> </ul>

Dataset irds.msmarco-document.trec-dl-hard.fold1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 1 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 1 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 1 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 2 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 2 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 2 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 3 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 3 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold3

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 3 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold4.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 4 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold4.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 4 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold4

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 4 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold5.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Fold 5 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold5.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Fold 5 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Dataset irds.msmarco-document.trec-dl-hard.fold5

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Fold 5 of <a class=”ds-ref”>msmarco-document/trec-dl-hard</a> </p>

Anchor Text for Version 1 of MS MARCO

<p> For version 1 of MS MARCO, the anchor text collection enriches 1,703,834 documents with anchor text extracted from six Common Crawl snapshots. To keep the collection size reasonable, we sampled 1,000 anchor texts for documents with more than 1,000 anchor texts (this sampling yields that all anchor text is included for 94% of the documents). The <code>text</code> field contains the anchor texts concatenated and the <code>anchors</code> field contains the anchor texts as list. The raw dataset with additional information (roughly 100GB) is <a href=”https://github.com/webis-de/ecir22-anchor-text”>available online</a>. </p>

Dataset irds.msmarco-document.anchor-text.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> For version 1 of MS MARCO, the anchor text collection enriches 1,703,834 documents with anchor text extracted from six Common Crawl snapshots. To keep the collection size reasonable, we sampled 1,000 anchor texts for documents with more than 1,000 anchor texts (this sampling yields that all anchor text is included for 94% of the documents). The <code>text</code> field contains the anchor texts concatenated and the <code>anchors</code> field contains the anchor texts as list. The raw dataset with additional information (roughly 100GB) is <a href=”https://github.com/webis-de/ecir22-anchor-text”>available online</a>. </p>

MSMARCO (document, version 2)

<p> Version 2 of the MS MARCO document ranking dataset. The corpus contains 12M documents (roughly 3x as many as version 1). </p> <ul> <li>Version 1 of dataset: <a class=”ds-ref”>msmarco-document</a></li> <li>Documents: Text extracted from web pages</li> <li>Queries: Natural language questions (from query log)</li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-document-v2.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version 2 of the MS MARCO document ranking dataset. The corpus contains 12M documents (roughly 3x as many as version 1). </p> <ul> <li>Version 1 of dataset: <a class=”ds-ref”>msmarco-document</a></li> <li>Documents: Text extracted from web pages</li> <li>Queries: Natural language questions (from query log)</li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul>

Dataset irds.msmarco-document-v2.dev1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev1 set with 4,552 queries. </p>

Dataset irds.msmarco-document-v2.dev1.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official dev1 set with 4,552 queries. </p>

Dataset irds.msmarco-document-v2.dev1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev1 set with 4,552 queries. </p>

Dataset irds.msmarco-document-v2.dev1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev1 set with 4,552 queries. </p>

Dataset irds.msmarco-document-v2.dev2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev2 set with 5,000 queries. </p>

Dataset irds.msmarco-document-v2.dev2.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official dev2 set with 5,000 queries. </p>

Dataset irds.msmarco-document-v2.dev2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev2 set with 5,000 queries. </p>

Dataset irds.msmarco-document-v2.dev2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev2 set with 5,000 queries. </p>

Dataset irds.msmarco-document-v2.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set with 322,196 queries. </p>

Dataset irds.msmarco-document-v2.train.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official train set with 322,196 queries. </p>

Dataset irds.msmarco-document-v2.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set with 322,196 queries. </p>

Dataset irds.msmarco-document-v2.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set with 322,196 queries. </p>

Dataset irds.msmarco-document-v2.trec-dl-2019.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document-v2/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document-v2.trec-dl-2019.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document-v2/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document-v2.trec-dl-2019

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Queries from the TREC Deep Learning (DL) 2019 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document-v2/trec-dl-2019/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.07820.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document-v2.trec-dl-2019.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-document-v2/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2019.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-document-v2/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2019.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-document-v2/trec-dl-2019</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2020.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document-v2/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document-v2.trec-dl-2020.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document-v2/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document-v2.trec-dl-2020

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Queries from the TREC Deep Learning (DL) 2020 shared task, which were sampled from <a class=”ds-ref”>msmarco-document/eval</a>. A subset of these queries were judged by NIST assessors, (filtered list available in <a class=”ds-ref”>msmarco-document-v2/trec-dl-2020/judged</a>). </p> <ul> <li><a href=”https://arxiv.org/pdf/2102.07662.pdf”>Shared Task Paper</a></li> </ul>

Dataset irds.msmarco-document-v2.trec-dl-2020.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of <a class=”ds-ref”>msmarco-document-v2/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2020.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of <a class=”ds-ref”>msmarco-document-v2/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2020.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of <a class=”ds-ref”>msmarco-document-v2/trec-dl-2020</a>, only including queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2021.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official topics for the TREC Deep Learning (DL) 2021 shared task. </p> <p> Note that at this time, qrels are only available to those with TREC active participant login credentials. </p>

Dataset irds.msmarco-document-v2.trec-dl-2021.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official topics for the TREC Deep Learning (DL) 2021 shared task. </p> <p> Note that at this time, qrels are only available to those with TREC active participant login credentials. </p>

Dataset irds.msmarco-document-v2.trec-dl-2021.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official topics for the TREC Deep Learning (DL) 2021 shared task. </p> <p> Note that at this time, qrels are only available to those with TREC active participant login credentials. </p>

Dataset irds.msmarco-document-v2.trec-dl-2021

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official topics for the TREC Deep Learning (DL) 2021 shared task. </p> <p> Note that at this time, qrels are only available to those with TREC active participant login credentials. </p>

Dataset irds.msmarco-document-v2.trec-dl-2021.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>msmarco-document-v2/trec-dl-2021</a>, but filtered down to the 57 queries with qrels. </p> <p> Note that at this time, this is only available to those with TREC active participant login credentials. </p>

Dataset irds.msmarco-document-v2.trec-dl-2021.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> <a class=”ds-ref”>msmarco-document-v2/trec-dl-2021</a>, but filtered down to the 57 queries with qrels. </p> <p> Note that at this time, this is only available to those with TREC active participant login credentials. </p>

Dataset irds.msmarco-document-v2.trec-dl-2021.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>msmarco-document-v2/trec-dl-2021</a>, but filtered down to the 57 queries with qrels. </p> <p> Note that at this time, this is only available to those with TREC active participant login credentials. </p>

Dataset irds.msmarco-document-v2.trec-dl-2021.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>msmarco-document-v2/trec-dl-2021</a>, but filtered down to the 57 queries with qrels. </p> <p> Note that at this time, this is only available to those with TREC active participant login credentials. </p>

Dataset irds.msmarco-document-v2.trec-dl-2022.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official topics for the TREC Deep Learning (DL) 2022 shared task. </p> <p> Note that these qrels are <i>inferred</i> from the passage ranking task; a document’s relevance label is the maximum of the labels of its passages. </p>

Dataset irds.msmarco-document-v2.trec-dl-2022.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official topics for the TREC Deep Learning (DL) 2022 shared task. </p> <p> Note that these qrels are <i>inferred</i> from the passage ranking task; a document’s relevance label is the maximum of the labels of its passages. </p>

Dataset irds.msmarco-document-v2.trec-dl-2022.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official topics for the TREC Deep Learning (DL) 2022 shared task. </p> <p> Note that these qrels are <i>inferred</i> from the passage ranking task; a document’s relevance label is the maximum of the labels of its passages. </p>

Dataset irds.msmarco-document-v2.trec-dl-2022

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official topics for the TREC Deep Learning (DL) 2022 shared task. </p> <p> Note that these qrels are <i>inferred</i> from the passage ranking task; a document’s relevance label is the maximum of the labels of its passages. </p>

Dataset irds.msmarco-document-v2.trec-dl-2022.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>msmarco-document-v2/trec-dl-2022</a>, but filtered down to only the queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2022.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> <a class=”ds-ref”>msmarco-document-v2/trec-dl-2022</a>, but filtered down to only the queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2022.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>msmarco-document-v2/trec-dl-2022</a>, but filtered down to only the queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2022.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>msmarco-document-v2/trec-dl-2022</a>, but filtered down to only the queries with qrels. </p>

Dataset irds.msmarco-document-v2.trec-dl-2023.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official topics for the TREC Deep Learning (DL) 2023 shared task. </p>

Dataset irds.msmarco-document-v2.trec-dl-2023.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official topics for the TREC Deep Learning (DL) 2023 shared task. </p>

Anchor Text for version 2 of MS Marco

<p> For version 2 of MS MARCO, the anchor text collection enriches 4,821,244 documents with anchor text extracted from six Common Crawl snapshots. To keep the collection size reasonable, we sampled 1,000 anchor texts for documents with more than 1,000 anchor texts (this sampling yields that all anchor text is included for 97% of the documents). The <code>text</code> field contains the anchor texts concatenated and the <code>anchors</code> field contains the anchor texts as list. The raw dataset with additional information (roughly 100GB) is <a href=”https://github.com/webis-de/ecir22-anchor-text”>available online</a>. </p>

Dataset irds.msmarco-document-v2.anchor-text.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> For version 2 of MS MARCO, the anchor text collection enriches 4,821,244 documents with anchor text extracted from six Common Crawl snapshots. To keep the collection size reasonable, we sampled 1,000 anchor texts for documents with more than 1,000 anchor texts (this sampling yields that all anchor text is included for 97% of the documents). The <code>text</code> field contains the anchor texts concatenated and the <code>anchors</code> field contains the anchor texts as list. The raw dataset with additional information (roughly 100GB) is <a href=”https://github.com/webis-de/ecir22-anchor-text”>available online</a>. </p>

MSMARCO (passage, version 2)

<p> Version 2 of the MS MARCO passage ranking dataset. The corpus contains 138M passages, which can be linked up with documents in <a class=”ds-ref”>msmarco-document-v2</a>. </p> <ul> <li>Version 1 of dataset: <a class=”ds-ref”>msmarco-passage</a></li> <li>Documents: Text extracted from web pages</li> <li>Queries: Natural language questions (from query log)</li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul> <p> Change Log </p> <ul> <li> On July 21, 2021, the task organizers <a href=”https://github.com/microsoft/msmarco/commit/41b3a684ed8ebd4e753250c3687547a77c62e7dd”> updated the train, dev1, and dev2 qrels</a> to remove duplicate entries from the files. This should not have change results from evaluation tools, but may result in non-repeatable results if these files were used in another process (e.g., model training). The original qrels file for <a class=”ds-ref”>msmarco-passage-v2/train</a> can be found <a href=”https://mirror.ir-datasets.com/abf1fd024b6aca203364d2138c241a6d”>here</a> to aid in result repeatability. </li> </ul>

Dataset irds.msmarco-passage-v2.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version 2 of the MS MARCO passage ranking dataset. The corpus contains 138M passages, which can be linked up with documents in <a class=”ds-ref”>msmarco-document-v2</a>. </p> <ul> <li>Version 1 of dataset: <a class=”ds-ref”>msmarco-passage</a></li> <li>Documents: Text extracted from web pages</li> <li>Queries: Natural language questions (from query log)</li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> </ul> <p> Change Log </p> <ul> <li> On July 21, 2021, the task organizers <a href=”https://github.com/microsoft/msmarco/commit/41b3a684ed8ebd4e753250c3687547a77c62e7dd”> updated the train, dev1, and dev2 qrels</a> to remove duplicate entries from the files. This should not have change results from evaluation tools, but may result in non-repeatable results if these files were used in another process (e.g., model training). The original qrels file for <a class=”ds-ref”>msmarco-passage-v2/train</a> can be found <a href=”https://mirror.ir-datasets.com/abf1fd024b6aca203364d2138c241a6d”>here</a> to aid in result repeatability. </li> </ul>

Dataset irds.msmarco-passage-v2.dev1.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev1 set with 3,903 queries. </p> <p> Note that that qrels in this dataset are not directly human-assessed; labels from <a class=”ds-ref”>msmarco-passage</a> are mapped to documents via URL, these documents are re-passaged, and then the best approximate match is identified. </p>

Dataset irds.msmarco-passage-v2.dev1.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official dev1 set with 3,903 queries. </p> <p> Note that that qrels in this dataset are not directly human-assessed; labels from <a class=”ds-ref”>msmarco-passage</a> are mapped to documents via URL, these documents are re-passaged, and then the best approximate match is identified. </p>

Dataset irds.msmarco-passage-v2.dev1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev1 set with 3,903 queries. </p> <p> Note that that qrels in this dataset are not directly human-assessed; labels from <a class=”ds-ref”>msmarco-passage</a> are mapped to documents via URL, these documents are re-passaged, and then the best approximate match is identified. </p>

Dataset irds.msmarco-passage-v2.dev1

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev1 set with 3,903 queries. </p> <p> Note that that qrels in this dataset are not directly human-assessed; labels from <a class=”ds-ref”>msmarco-passage</a> are mapped to documents via URL, these documents are re-passaged, and then the best approximate match is identified. </p>

Dataset irds.msmarco-passage-v2.dev2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev2 set with 4,281 queries. </p> <p> Note that that qrels in this dataset are not directly human-assessed; labels from <a class=”ds-ref”>msmarco-passage</a> are mapped to documents via URL, these documents are re-passaged, and then the best approximate match is identified. </p>

Dataset irds.msmarco-passage-v2.dev2.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official dev2 set with 4,281 queries. </p> <p> Note that that qrels in this dataset are not directly human-assessed; labels from <a class=”ds-ref”>msmarco-passage</a> are mapped to documents via URL, these documents are re-passaged, and then the best approximate match is identified. </p>

Dataset irds.msmarco-passage-v2.dev2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev2 set with 4,281 queries. </p> <p> Note that that qrels in this dataset are not directly human-assessed; labels from <a class=”ds-ref”>msmarco-passage</a> are mapped to documents via URL, these documents are re-passaged, and then the best approximate match is identified. </p>

Dataset irds.msmarco-passage-v2.dev2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev2 set with 4,281 queries. </p> <p> Note that that qrels in this dataset are not directly human-assessed; labels from <a class=”ds-ref”>msmarco-passage</a> are mapped to documents via URL, these documents are re-passaged, and then the best approximate match is identified. </p>

Dataset irds.msmarco-passage-v2.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set with 277,144 queries. </p>

Dataset irds.msmarco-passage-v2.train.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official train set with 277,144 queries. </p>

Dataset irds.msmarco-passage-v2.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set with 277,144 queries. </p>

Dataset irds.msmarco-passage-v2.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set with 277,144 queries. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2021.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official topics for the TREC Deep Learning (DL) 2021 shared task. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2021.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official topics for the TREC Deep Learning (DL) 2021 shared task. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2021.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official topics for the TREC Deep Learning (DL) 2021 shared task. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2021

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official topics for the TREC Deep Learning (DL) 2021 shared task. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2021.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>msmarco-passage-v2/trec-dl-2021</a>, but filtered down to the 53 queries with qrels. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2021.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> <a class=”ds-ref”>msmarco-passage-v2/trec-dl-2021</a>, but filtered down to the 53 queries with qrels. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2021.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>msmarco-passage-v2/trec-dl-2021</a>, but filtered down to the 53 queries with qrels. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2021.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>msmarco-passage-v2/trec-dl-2021</a>, but filtered down to the 53 queries with qrels. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2022.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official topics for the TREC Deep Learning (DL) 2022 shared task. </p> <p> Note that the officially-released qrels <i>include</i> relevance labels propagated to duplicate passages, while results presented in the notebook papers remove duplicate documents. This means that the results are not directly comparable, and extra care should be taken when making comparisions among systems to ensure that they were evaluated in the same settings. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2022.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official topics for the TREC Deep Learning (DL) 2022 shared task. </p> <p> Note that the officially-released qrels <i>include</i> relevance labels propagated to duplicate passages, while results presented in the notebook papers remove duplicate documents. This means that the results are not directly comparable, and extra care should be taken when making comparisions among systems to ensure that they were evaluated in the same settings. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2022.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official topics for the TREC Deep Learning (DL) 2022 shared task. </p> <p> Note that the officially-released qrels <i>include</i> relevance labels propagated to duplicate passages, while results presented in the notebook papers remove duplicate documents. This means that the results are not directly comparable, and extra care should be taken when making comparisions among systems to ensure that they were evaluated in the same settings. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2022

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official topics for the TREC Deep Learning (DL) 2022 shared task. </p> <p> Note that the officially-released qrels <i>include</i> relevance labels propagated to duplicate passages, while results presented in the notebook papers remove duplicate documents. This means that the results are not directly comparable, and extra care should be taken when making comparisions among systems to ensure that they were evaluated in the same settings. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2022.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>msmarco-passage-v2/trec-dl-2022</a>, but filtered down to only the queries with qrels. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2022.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> <a class=”ds-ref”>msmarco-passage-v2/trec-dl-2022</a>, but filtered down to only the queries with qrels. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2022.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>msmarco-passage-v2/trec-dl-2022</a>, but filtered down to only the queries with qrels. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2022.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>msmarco-passage-v2/trec-dl-2022</a>, but filtered down to only the queries with qrels. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2023.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official topics for the TREC Deep Learning (DL) 2023 shared task. </p>

Dataset irds.msmarco-passage-v2.trec-dl-2023.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official topics for the TREC Deep Learning (DL) 2023 shared task. </p>

msmarco-passage-v2/dedup

Dataset irds.msmarco-passage-v2.dedup.documents

→ datamaestro_text.datasets.irds.data.Documents

MSMARCO (QnA)

<p> The MS MARCO Question Answering dataset. This is the source collection of <a class=”ds-ref”>msmarco-passage</a> and <a class=”ds-ref”>msmarco-document</a>. </p> <div class=”warn”> It is prohibited to use information from this dataset for submissions to the MS MARCO passage and document leaderboards or the TREC DL shared task. </div> <p> Query IDs in this collection align with those found in <a class=”ds-ref”>msmarco-passage</a> and <a class=”ds-ref”>msmarco-document</a>. The collection does not provide doc_ids, so these are assigned in the following format: <code>[msmarco_passage_id]-[url_seq]</code>, where <code>[msmarco_passage_id]</code> is the document from <a class=”ds-ref”>msmarco-passage</a> that has matching contents and <code>[url_seq]</code> is assigned sequentially for each URL encountered. In other words, all documents with the same prefix have the same text; they only differ in the originating document. </p> <p> Doc <code>msmarco_passage_id</code> fields are assigned by matching pasasge contents in <a class=”ds-ref”>msmarco-passage</a>, and this field is provided for every document. Doc <code>msmarco_document_id</code> fields are assigned by matching the URL to the one found in <a class=”ds-ref”>msmarco-document</a>. Due to how <a class=”ds-ref”>msmarco-document</a> was constructed, there is not necessarily a match (value will be <code class=”kwd”>None</code> if no match). </p> <ul> <li>Documents: Short passages (from web)</li> <li>Queries: Natural language questions (from query log), including type and natural-language answers.</li> <li><a href=”https://microsoft.github.io/msmarco/#qna”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li><a href=”https://github.com/microsoft/MSMARCO-Question-Answering”>More information</a></li> </ul>

Dataset irds.msmarco-qna.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The MS MARCO Question Answering dataset. This is the source collection of <a class=”ds-ref”>msmarco-passage</a> and <a class=”ds-ref”>msmarco-document</a>. </p> <div class=”warn”> It is prohibited to use information from this dataset for submissions to the MS MARCO passage and document leaderboards or the TREC DL shared task. </div> <p> Query IDs in this collection align with those found in <a class=”ds-ref”>msmarco-passage</a> and <a class=”ds-ref”>msmarco-document</a>. The collection does not provide doc_ids, so these are assigned in the following format: <code>[msmarco_passage_id]-[url_seq]</code>, where <code>[msmarco_passage_id]</code> is the document from <a class=”ds-ref”>msmarco-passage</a> that has matching contents and <code>[url_seq]</code> is assigned sequentially for each URL encountered. In other words, all documents with the same prefix have the same text; they only differ in the originating document. </p> <p> Doc <code>msmarco_passage_id</code> fields are assigned by matching pasasge contents in <a class=”ds-ref”>msmarco-passage</a>, and this field is provided for every document. Doc <code>msmarco_document_id</code> fields are assigned by matching the URL to the one found in <a class=”ds-ref”>msmarco-document</a>. Due to how <a class=”ds-ref”>msmarco-document</a> was constructed, there is not necessarily a match (value will be <code class=”kwd”>None</code> if no match). </p> <ul> <li>Documents: Short passages (from web)</li> <li>Queries: Natural language questions (from query log), including type and natural-language answers.</li> <li><a href=”https://microsoft.github.io/msmarco/#qna”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li><a href=”https://github.com/microsoft/MSMARCO-Question-Answering”>More information</a></li> </ul>

Dataset irds.msmarco-qna.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.dev.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official dev set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.eval.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official eval set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.eval.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official eval set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.train.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official train set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

Dataset irds.msmarco-qna.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set. </p> <p> The scoreddocs provides the roughtly 10 passages presented to the user for annotation, where the score indicates the order presented. </p>

nano-beir/arguana

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.arguana.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.arguana.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.arguana.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.arguana

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the ArguAna Counterargs dataset, for argument retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/P18-1023.pdf”>Dataset paper</a></li> <li><a href=”http://argumentation.bplaced.net/arguana/data”>Dataset website</a></li> </ul>

nano-beir/climate-fever

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.climate-fever.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.climate-fever.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.climate-fever.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.climate-fever

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the CLIMATE-FEVER dataset, for fact verification on claims about climate. </p> <ul> <li><a href=”https://arxiv.org/pdf/2012.00614.pdf”>Dataset paper</a></li> <li><a href=”https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html”>Dataset website</a></li> </ul>

nano-beir/dbpedia-entity

<p> A version of the DBPedia-Entity-v2 dataset for entity retrieval. </p> <ul> <li><a href=”http://hasibi.com/files/sigir2017-dbpedia_entity.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/iai-group/DBpedia-Entity”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.dbpedia-entity.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the DBPedia-Entity-v2 dataset for entity retrieval. </p> <ul> <li><a href=”http://hasibi.com/files/sigir2017-dbpedia_entity.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/iai-group/DBpedia-Entity”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.dbpedia-entity.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the DBPedia-Entity-v2 dataset for entity retrieval. </p> <ul> <li><a href=”http://hasibi.com/files/sigir2017-dbpedia_entity.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/iai-group/DBpedia-Entity”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.dbpedia-entity.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the DBPedia-Entity-v2 dataset for entity retrieval. </p> <ul> <li><a href=”http://hasibi.com/files/sigir2017-dbpedia_entity.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/iai-group/DBpedia-Entity”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.dbpedia-entity

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the DBPedia-Entity-v2 dataset for entity retrieval. </p> <ul> <li><a href=”http://hasibi.com/files/sigir2017-dbpedia_entity.pdf”>Dataset paper</a></li> <li><a href=”https://github.com/iai-group/DBpedia-Entity”>Dataset website</a></li> </ul>

nano-beir/fever

<p> A version of the FEVER dataset for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/N18-1074.pdf”>Dataset paper</a></li> <li><a href=”https://fever.ai/resources.html”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.fever.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the FEVER dataset for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/N18-1074.pdf”>Dataset paper</a></li> <li><a href=”https://fever.ai/resources.html”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.fever.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the FEVER dataset for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/N18-1074.pdf”>Dataset paper</a></li> <li><a href=”https://fever.ai/resources.html”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.fever.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the FEVER dataset for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/N18-1074.pdf”>Dataset paper</a></li> <li><a href=”https://fever.ai/resources.html”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.fever

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the FEVER dataset for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/N18-1074.pdf”>Dataset paper</a></li> <li><a href=”https://fever.ai/resources.html”>Dataset website</a></li> </ul>

nano-beir/fiqa

<p> A version of the FIQA-2018 dataset (financial opinion question answering). </p> <ul> <li><a href=”https://dl.acm.org/doi/10.1145/3184558.3192301”>Dataset paper</a></li> <li><a href=”https://sites.google.com/view/fiqa/home”>Dataset site</a></li> </ul>

Dataset irds.nano-beir.fiqa.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the FIQA-2018 dataset (financial opinion question answering). </p> <ul> <li><a href=”https://dl.acm.org/doi/10.1145/3184558.3192301”>Dataset paper</a></li> <li><a href=”https://sites.google.com/view/fiqa/home”>Dataset site</a></li> </ul>

Dataset irds.nano-beir.fiqa.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the FIQA-2018 dataset (financial opinion question answering). </p> <ul> <li><a href=”https://dl.acm.org/doi/10.1145/3184558.3192301”>Dataset paper</a></li> <li><a href=”https://sites.google.com/view/fiqa/home”>Dataset site</a></li> </ul>

Dataset irds.nano-beir.fiqa.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the FIQA-2018 dataset (financial opinion question answering). </p> <ul> <li><a href=”https://dl.acm.org/doi/10.1145/3184558.3192301”>Dataset paper</a></li> <li><a href=”https://sites.google.com/view/fiqa/home”>Dataset site</a></li> </ul>

Dataset irds.nano-beir.fiqa

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the FIQA-2018 dataset (financial opinion question answering). </p> <ul> <li><a href=”https://dl.acm.org/doi/10.1145/3184558.3192301”>Dataset paper</a></li> <li><a href=”https://sites.google.com/view/fiqa/home”>Dataset site</a></li> </ul>

nano-beir/hotpotqa

<p> A version of the Hotpot QA dataset for multi-hop question answering. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/D18-1259”>Dataset paper</a></li> <li><a href=”https://github.com/hotpotqa/hotpot”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.hotpotqa.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the Hotpot QA dataset for multi-hop question answering. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/D18-1259”>Dataset paper</a></li> <li><a href=”https://github.com/hotpotqa/hotpot”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.hotpotqa.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the Hotpot QA dataset for multi-hop question answering. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/D18-1259”>Dataset paper</a></li> <li><a href=”https://github.com/hotpotqa/hotpot”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.hotpotqa.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the Hotpot QA dataset for multi-hop question answering. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/D18-1259”>Dataset paper</a></li> <li><a href=”https://github.com/hotpotqa/hotpot”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.hotpotqa

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the Hotpot QA dataset for multi-hop question answering. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/D18-1259”>Dataset paper</a></li> <li><a href=”https://github.com/hotpotqa/hotpot”>Dataset website</a></li> </ul>

nano-beir/msmarco

<p> A version of the MS MARCO passage ranking dataset. </p> <p> Note that this version differs from <a class=”ds-ref”>msmarco-passage</a>, in that it does not correct the encoding problems in the source documents. </p> <ul> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> </ul>

Dataset irds.nano-beir.msmarco.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the MS MARCO passage ranking dataset. </p> <p> Note that this version differs from <a class=”ds-ref”>msmarco-passage</a>, in that it does not correct the encoding problems in the source documents. </p> <ul> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> </ul>

Dataset irds.nano-beir.msmarco.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the MS MARCO passage ranking dataset. </p> <p> Note that this version differs from <a class=”ds-ref”>msmarco-passage</a>, in that it does not correct the encoding problems in the source documents. </p> <ul> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> </ul>

Dataset irds.nano-beir.msmarco.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the MS MARCO passage ranking dataset. </p> <p> Note that this version differs from <a class=”ds-ref”>msmarco-passage</a>, in that it does not correct the encoding problems in the source documents. </p> <ul> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> </ul>

Dataset irds.nano-beir.msmarco

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the MS MARCO passage ranking dataset. </p> <p> Note that this version differs from <a class=”ds-ref”>msmarco-passage</a>, in that it does not correct the encoding problems in the source documents. </p> <ul> <li><a href=”https://microsoft.github.io/msmarco/#ranking”>Leaderboard</a></li> <li><a href=”https://arxiv.org/abs/1611.09268”>Dataset Paper</a></li> <li>See also: <a class=”ds-ref”>msmarco-passage</a></li> </ul>

nano-beir/nfcorpus

<p> A version of the NF Corpus (Nutrition Facts). </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>nfcorpus</a>. </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> <li>See also: <a class=”ds-ref”>nfcorpus</a></li> </ul>

Dataset irds.nano-beir.nfcorpus.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the NF Corpus (Nutrition Facts). </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>nfcorpus</a>. </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> <li>See also: <a class=”ds-ref”>nfcorpus</a></li> </ul>

Dataset irds.nano-beir.nfcorpus.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the NF Corpus (Nutrition Facts). </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>nfcorpus</a>. </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> <li>See also: <a class=”ds-ref”>nfcorpus</a></li> </ul>

Dataset irds.nano-beir.nfcorpus.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the NF Corpus (Nutrition Facts). </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>nfcorpus</a>. </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> <li>See also: <a class=”ds-ref”>nfcorpus</a></li> </ul>

Dataset irds.nano-beir.nfcorpus

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the NF Corpus (Nutrition Facts). </p> <p> Data pre-processing may be different than what is done in <a class=”ds-ref”>nfcorpus</a>. </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> <li>See also: <a class=”ds-ref”>nfcorpus</a></li> </ul>

nano-beir/nq

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

Dataset irds.nano-beir.nq.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

Dataset irds.nano-beir.nq.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

Dataset irds.nano-beir.nq.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

Dataset irds.nano-beir.nq

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the Natural Questions dev dataset. </p> <p> Data pre-processing differs both from what is done in <a class=”ds-ref”>natural-questions</a> and <a class=”ds-ref”>dpr-w100/natural-questions</a>, especially with respect to the document collection and filtering conducted on the queries. See the Beir paper for details. </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>natural-questions</a>, <a class=”ds-ref”>dpr-w100/natural-questions</a></li> </ul>

nano-beir/quora

<p> A version of the Quora duplicate question detection dataset (QQP). </p> <ul> <li><a href=”https://www.kaggle.com/c/quora-question-pairs”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.quora.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the Quora duplicate question detection dataset (QQP). </p> <ul> <li><a href=”https://www.kaggle.com/c/quora-question-pairs”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.quora.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the Quora duplicate question detection dataset (QQP). </p> <ul> <li><a href=”https://www.kaggle.com/c/quora-question-pairs”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.quora.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the Quora duplicate question detection dataset (QQP). </p> <ul> <li><a href=”https://www.kaggle.com/c/quora-question-pairs”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.quora

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the Quora duplicate question detection dataset (QQP). </p> <ul> <li><a href=”https://www.kaggle.com/c/quora-question-pairs”>Dataset website</a></li> </ul>

nano-beir/scidocs

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.scidocs.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.scidocs.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.scidocs.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.scidocs

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the SciDocs dataset, used for citation retrieval. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.acl-main.207.pdf”>Dataset paper</a></li> <li><a href=”https://allenai.org/data/scidocs”>Dataset website</a></li> </ul>

nano-beir/scifact

<p> A version of the SciFact dataset, for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset paper</a></li> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.scifact.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A version of the SciFact dataset, for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset paper</a></li> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.scifact.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of the SciFact dataset, for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset paper</a></li> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.scifact.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of the SciFact dataset, for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset paper</a></li> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset website</a></li> </ul>

Dataset irds.nano-beir.scifact

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of the SciFact dataset, for fact verification. </p> <ul> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset paper</a></li> <li><a href=”https://www.aclweb.org/anthology/2020.emnlp-main.609.pdf”>Dataset website</a></li> </ul>

nano-beir/webis-touche2020

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.nano-beir.webis-touche2020.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.nano-beir.webis-touche2020.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.nano-beir.webis-touche2020.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

Dataset irds.nano-beir.webis-touche2020

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Original version of the Touchè-2020 dataset, for argument retrieval. </p> <div class=”warn”> Consider using <a class=”ds-ref”>beir/webis-touche2020/v2</a> instead; it uses an updated, more complete version of the qrels. </div> <ul> <li><a href=”https://link.springer.com/chapter/10.1007%2F978-3-030-58219-7_26”>Dataset paper</a></li> <li><a href=”https://webis.de/events/touche-20/”>Dataset webiste</a></li> </ul>

neumarco/fa

<p>The <a class=”ds-ref”>msmarco-passage</a> corpus, translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.documents

→ datamaestro_text.datasets.irds.data.Documents

<p>The <a class=”ds-ref”>msmarco-passage</a> corpus, translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.train.docpairs

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.train.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.train.judged.docpairs

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.train.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Persian (Farsi).</p>

Dataset irds.neumarco.fa.train.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Persian (Farsi).</p>

neumarco/ru

<p>The <a class=”ds-ref”>msmarco-passage</a> corpus, translated to Russian.</p>

Dataset irds.neumarco.ru.documents

→ datamaestro_text.datasets.irds.data.Documents

<p>The <a class=”ds-ref”>msmarco-passage</a> corpus, translated to Russian.</p>

Dataset irds.neumarco.ru.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.dev.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.dev.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.dev.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.train.docpairs

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.train.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.train.judged.docpairs

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.train.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Russian.</p>

Dataset irds.neumarco.ru.train.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Russian.</p>

neumarco/zh

<p>The <a class=”ds-ref”>msmarco-passage</a> corpus, translated to Chinese.</p>

Dataset irds.neumarco.zh.documents

→ datamaestro_text.datasets.irds.data.Documents

<p>The <a class=”ds-ref”>msmarco-passage</a> corpus, translated to Chinese.</p>

Dataset irds.neumarco.zh.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.dev.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.dev.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.dev.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/judged</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.dev.small.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.dev.small.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.dev.small

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/dev/small</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.train.docpairs

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/train</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.train.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.train.judged.docpairs

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.train.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Chinese.</p>

Dataset irds.neumarco.zh.train.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p>A version of <a class=”ds-ref”>msmarco-passage/train/judged</a>, with the corpus translated to Chinese.</p>

NFCorpus (NutritionFacts)

<p> “NFCorpus is a full-text English retrieval data set for Medical Information Retrieval. It contains a total of 3,244 natural language queries (written in non-technical English, harvested from the NutritionFacts.org site) with 169,756 automatically extracted relevance judgments for 9,964 medical documents (written in a complex terminology-heavy language), mostly from PubMed.” </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> </ul>

Dataset irds.nfcorpus.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> “NFCorpus is a full-text English retrieval data set for Medical Information Retrieval. It contains a total of 3,244 natural language queries (written in non-technical English, harvested from the NutritionFacts.org site) with 169,756 automatically extracted relevance judgments for 9,964 medical documents (written in a complex terminology-heavy language), mostly from PubMed.” </p> <ul> <li><a href=”https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/”>Dataset website</p></li> <li><a href=”https://link.springer.com/chapter/10.1007/978-3-319-30671-1_58”>Dataset paper</p></li> </ul>

Dataset irds.nfcorpus.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.dev.nontopic.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.dev.nontopic.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.dev.nontopic

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.dev.video.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev set, filtered to only include queries from video pages. </p>

Dataset irds.nfcorpus.dev.video.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev set, filtered to only include queries from video pages. </p>

Dataset irds.nfcorpus.dev.video

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev set, filtered to only include queries from video pages. </p>

Dataset irds.nfcorpus.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.test.nontopic.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.test.nontopic.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.test.nontopic

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.test.video.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official test set, filtered to only include queries from video pages. </p>

Dataset irds.nfcorpus.test.video.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official test set, filtered to only include queries from video pages. </p>

Dataset irds.nfcorpus.test.video

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official test set, filtered to only include queries from video pages. </p>

Dataset irds.nfcorpus.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set. Queries include both title and combinted “all” text field (titles, descriptions, topics, transcripts and comments) </p>

Dataset irds.nfcorpus.train.nontopic.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.train.nontopic.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.train.nontopic

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set, filtered to exclude queries from topic pages. </p>

Dataset irds.nfcorpus.train.video.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set, filtered to only include queries from video pages. </p>

Dataset irds.nfcorpus.train.video.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set, filtered to only include queries from video pages. </p>

Dataset irds.nfcorpus.train.video

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set, filtered to only include queries from video pages. </p>

Natural Questions

<p> Google Natural Questions is a Q&amp;A dataset containing long, short, and Yes/No answers from Wikipedia. <kbd>ir_datasets</kbd> frames this around an ad-hoc ranking setting by building a collection of all long answer candidate passages. However, short and Yes/No annotations are also available in the <kbd>qrels</kbd>, as are the passages presented to the annotators (via <kbd>scoreddocs</kbd>). </p> <p> Importantly, the document collection does not consist of all Wikipedia passages, but instead a union of the candidate passages presented to the annotators (akin to MS MARCO). <a class=”ds-ref”>dph-w100/natural-questions/train</a> and <a class=”ds-ref”>dph-w100/natural-questions/dev</a> contain a filtered set of the questions in this dataset and a full Wikipedia dump (which is a more realistic retrieval setting). </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>dph-w100</a></li> </ul>

Dataset irds.natural-questions.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Google Natural Questions is a Q&amp;A dataset containing long, short, and Yes/No answers from Wikipedia. <kbd>ir_datasets</kbd> frames this around an ad-hoc ranking setting by building a collection of all long answer candidate passages. However, short and Yes/No annotations are also available in the <kbd>qrels</kbd>, as are the passages presented to the annotators (via <kbd>scoreddocs</kbd>). </p> <p> Importantly, the document collection does not consist of all Wikipedia passages, but instead a union of the candidate passages presented to the annotators (akin to MS MARCO). <a class=”ds-ref”>dph-w100/natural-questions/train</a> and <a class=”ds-ref”>dph-w100/natural-questions/dev</a> contain a filtered set of the questions in this dataset and a full Wikipedia dump (which is a more realistic retrieval setting). </p> <ul> <li><a href=”https://ai.google.com/research/NaturalQuestions”>Dataset website</a></li> <li><a href=”https://storage.googleapis.com/pub-tools-public-publication-data/pdf/1f7b46b5378d757553d3e92ead36bda2e4254244.pdf”>Dataset paper</a></li> <li>See also: <a class=”ds-ref”>dph-w100</a></li> </ul>

Dataset irds.natural-questions.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official dev set. </p>

Dataset irds.natural-questions.dev.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official dev set. </p>

Dataset irds.natural-questions.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official dev set. </p>

Dataset irds.natural-questions.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official dev set. </p>

Dataset irds.natural-questions.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official train set. </p>

Dataset irds.natural-questions.train.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official train set. </p>

Dataset irds.natural-questions.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official train set. </p>

Dataset irds.natural-questions.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official train set. </p>

NYT

<p> The New York Times Annotated Corpus. Consists of articles published between 1987 and 2007. It is used in TREC Core 2017 and it is also useful for transferring relevance signals in cases where training data is in short supply. </p> <p> Uses data from <a href=”https://catalog.ldc.upenn.edu/LDC2008T19”>LDC2008T19</a>. The source collection can be downloaded from the LDC. </p>

Dataset irds.nyt.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The New York Times Annotated Corpus. Consists of articles published between 1987 and 2007. It is used in TREC Core 2017 and it is also useful for transferring relevance signals in cases where training data is in short supply. </p> <p> Uses data from <a href=”https://catalog.ldc.upenn.edu/LDC2008T19”>LDC2008T19</a>. The source collection can be downloaded from the LDC. </p>

Dataset irds.nyt.trec-core-2017.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Common Core 2017 benchmark. </p> <p> Note that this dataset only contains the 50 queries assessed by NIST. </p> <ul> <li>Queries: TREC-style (keyword, description, narrative)</li> <li>Relevance: Deeply-annotated</li> <li><a href=”https://github.com/trec-core/2017”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-CC.pdf”>Shared Task Paper</a></li> <ul>

Dataset irds.nyt.trec-core-2017.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Common Core 2017 benchmark. </p> <p> Note that this dataset only contains the 50 queries assessed by NIST. </p> <ul> <li>Queries: TREC-style (keyword, description, narrative)</li> <li>Relevance: Deeply-annotated</li> <li><a href=”https://github.com/trec-core/2017”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-CC.pdf”>Shared Task Paper</a></li> <ul>

Dataset irds.nyt.trec-core-2017

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Common Core 2017 benchmark. </p> <p> Note that this dataset only contains the 50 queries assessed by NIST. </p> <ul> <li>Queries: TREC-style (keyword, description, narrative)</li> <li>Relevance: Deeply-annotated</li> <li><a href=”https://github.com/trec-core/2017”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec26/papers/Overview-CC.pdf”>Shared Task Paper</a></li> <ul>

Dataset irds.nyt.wksup.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set (without held-out <a class=”ds-ref”>nyt/wksup/valid</a>) for transferring relevance signals from NYT corpus. </p>

Dataset irds.nyt.wksup.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set (without held-out <a class=”ds-ref”>nyt/wksup/valid</a>) for transferring relevance signals from NYT corpus. </p>

Dataset irds.nyt.wksup

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set (without held-out <a class=”ds-ref”>nyt/wksup/valid</a>) for transferring relevance signals from NYT corpus. </p>

Dataset irds.nyt.wksup.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set (without held-out <a class=”ds-ref”>nyt/wksup/valid</a>) for transferring relevance signals from NYT corpus. </p>

Dataset irds.nyt.wksup.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set (without held-out <a class=”ds-ref”>nyt/wksup/valid</a>) for transferring relevance signals from NYT corpus. </p>

Dataset irds.nyt.wksup.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set (without held-out <a class=”ds-ref”>nyt/wksup/valid</a>) for transferring relevance signals from NYT corpus. </p>

Dataset irds.nyt.wksup.valid.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Held-out validation set for transferring relevance signals from NYT corpus (see <a class=”ds-ref”>nyt/wksup/train</a>). </p>

Dataset irds.nyt.wksup.valid.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Held-out validation set for transferring relevance signals from NYT corpus (see <a class=”ds-ref”>nyt/wksup/train</a>). </p>

Dataset irds.nyt.wksup.valid

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Held-out validation set for transferring relevance signals from NYT corpus (see <a class=”ds-ref”>nyt/wksup/train</a>). </p>

pmc/v1

<p> Subset of PMC articles used for the TREC 2014 and 2015 tasks (v1). Inclues titles, abstracts, full text. Collected from the open access segment on January 21, 2014. </p> <ul> <li><a href=”http://www.trec-cds.org/2014.html#documents”>Information on documents</a></li> <ul>

Dataset irds.pmc.v1.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of PMC articles used for the TREC 2014 and 2015 tasks (v1). Inclues titles, abstracts, full text. Collected from the open access segment on January 21, 2014. </p> <ul> <li><a href=”http://www.trec-cds.org/2014.html#documents”>Information on documents</a></li> <ul>

Dataset irds.pmc.v1.trec-cds-2014.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Clinical Decision Support (CDS) track from 2014. </p> <ul> <li><a href=”http://www.trec-cds.org/2014.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec23/papers/overview-clinical.pdf”>Task Overview Paper</a></li> <ul>

Dataset irds.pmc.v1.trec-cds-2014.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Clinical Decision Support (CDS) track from 2014. </p> <ul> <li><a href=”http://www.trec-cds.org/2014.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec23/papers/overview-clinical.pdf”>Task Overview Paper</a></li> <ul>

Dataset irds.pmc.v1.trec-cds-2014

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Clinical Decision Support (CDS) track from 2014. </p> <ul> <li><a href=”http://www.trec-cds.org/2014.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec23/papers/overview-clinical.pdf”>Task Overview Paper</a></li> <ul>

Dataset irds.pmc.v1.trec-cds-2015.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Clinical Decision Support (CDS) track from 2015. </p> <ul> <li><a href=”http://www.trec-cds.org/2015.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec24/papers/Overview-CL.pdf”>Task Overview Paper</a></li> <ul>

Dataset irds.pmc.v1.trec-cds-2015.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Clinical Decision Support (CDS) track from 2015. </p> <ul> <li><a href=”http://www.trec-cds.org/2015.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec24/papers/Overview-CL.pdf”>Task Overview Paper</a></li> <ul>

Dataset irds.pmc.v1.trec-cds-2015

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Clinical Decision Support (CDS) track from 2015. </p> <ul> <li><a href=”http://www.trec-cds.org/2015.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec24/papers/Overview-CL.pdf”>Task Overview Paper</a></li> <ul>

pmc/v2

<p> Subset of PMC articles used for the TREC 2016 task (v2). Inclues titles, abstracts, full text. Collected from the open access segment on March 28, 2016. </p> <ul> <li><a href=”http://www.trec-cds.org/2016.html#documents”>Information on documents</a></li> <ul>

Dataset irds.pmc.v2.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of PMC articles used for the TREC 2016 task (v2). Inclues titles, abstracts, full text. Collected from the open access segment on March 28, 2016. </p> <ul> <li><a href=”http://www.trec-cds.org/2016.html#documents”>Information on documents</a></li> <ul>

Dataset irds.pmc.v2.trec-cds-2016.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Clinical Decision Support (CDS) track from 2016. </p> <ul> <li><a href=”http://www.trec-cds.org/2016.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec25/papers/Overview-CL.pdf”>Task Overview Paper</a></li> <ul>

Dataset irds.pmc.v2.trec-cds-2016.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Clinical Decision Support (CDS) track from 2016. </p> <ul> <li><a href=”http://www.trec-cds.org/2016.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec25/papers/Overview-CL.pdf”>Task Overview Paper</a></li> <ul>

Dataset irds.pmc.v2.trec-cds-2016

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Clinical Decision Support (CDS) track from 2016. </p> <ul> <li><a href=”http://www.trec-cds.org/2016.html”>Shared task site</a></li> <li><a href=”https://trec.nist.gov/pubs/trec25/papers/Overview-CL.pdf”>Task Overview Paper</a></li> <ul>

Touché Image Search

<p> Corpus version 2022-06-13 with 23 841 images. It was released on June 13, 2022 on <a href=”https://zenodo.org/record/3734893”>Zenodo</a>. </p> <p> This collection is licensed with the <a href=”https://creativecommons.org/licenses/by/4.0/”>Creative Commons Attribution 4.0 International</a>. Individual rights to the content still apply. </p> <ul> <li><a href=”https://zenodo.org/record/6873575”>Zenodo</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/image-retrieval-for-arguments.html”>Touché 2022 task 3 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Touché 2022 lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.touche-image.2022-06-13.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Corpus version 2022-06-13 with 23 841 images. It was released on June 13, 2022 on <a href=”https://zenodo.org/record/3734893”>Zenodo</a>. </p> <p> This collection is licensed with the <a href=”https://creativecommons.org/licenses/by/4.0/”>Creative Commons Attribution 4.0 International</a>. Individual rights to the content still apply. </p> <ul> <li><a href=”https://zenodo.org/record/6873575”>Zenodo</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/image-retrieval-for-arguments.html”>Touché 2022 task 3 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Touché 2022 lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.touche-image.2022-06-13.touche-2022-task-3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a controversial topic, the task is to retrieve images (from <a class=”ds-ref”>touche-image/2022-06-13</a>) for each stance (pro/con) that show support for that stance. </p> <p> Systems are evaluated on Touché topics 1-50 by the ratio of images among the 20 retrieved images for each topic (10 images for each stance) that are all three: relevant to the topic, argumentative, and have the associated stance. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/image-retrieval-for-arguments.html”>Task 3 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.touche-image.2022-06-13.touche-2022-task-3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a controversial topic, the task is to retrieve images (from <a class=”ds-ref”>touche-image/2022-06-13</a>) for each stance (pro/con) that show support for that stance. </p> <p> Systems are evaluated on Touché topics 1-50 by the ratio of images among the 20 retrieved images for each topic (10 images for each stance) that are all three: relevant to the topic, argumentative, and have the associated stance. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/image-retrieval-for-arguments.html”>Task 3 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.touche-image.2022-06-13.touche-2022-task-3

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a controversial topic, the task is to retrieve images (from <a class=”ds-ref”>touche-image/2022-06-13</a>) for each stance (pro/con) that show support for that stance. </p> <p> Systems are evaluated on Touché topics 1-50 by the ratio of images among the 20 retrieved images for each topic (10 images for each stance) that are all three: relevant to the topic, argumentative, and have the associated stance. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/image-retrieval-for-arguments.html”>Task 3 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Touché 2022 Task 2: Argument Retrieval for Comparative Questions

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a comparative topic and a collection of documents, the task is to retrieve relevant argumentative passages for either compared object or for both and to detect their respective stances with respect to the object they talk about. </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <p> Additionally, classify the stance of the retrieved text passages towards the compared objects in questions. For instance, in the question <i>Who is a better friend, a cat or a dog?</i> the terms <i>cat</i> and <i>dog</i> are the comparison objects. An answer candidate like <i>Cats can be quite affectionate and attentive, and thus are good friends</i> should be classified as pro the <i>cat</i> object, while <i>Cats are less faithful than dogs</i> as supporting the <i>dog</i> object. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/argument-retrieval-for-comparative-questions.html”>Task 2 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.clueweb12.touche-2022-task-2.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a comparative topic and a collection of documents, the task is to retrieve relevant argumentative passages for either compared object or for both and to detect their respective stances with respect to the object they talk about. </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <p> Additionally, classify the stance of the retrieved text passages towards the compared objects in questions. For instance, in the question <i>Who is a better friend, a cat or a dog?</i> the terms <i>cat</i> and <i>dog</i> are the comparison objects. An answer candidate like <i>Cats can be quite affectionate and attentive, and thus are good friends</i> should be classified as pro the <i>cat</i> object, while <i>Cats are less faithful than dogs</i> as supporting the <i>dog</i> object. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/argument-retrieval-for-comparative-questions.html”>Task 2 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.clueweb12.touche-2022-task-2.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a comparative topic and a collection of documents, the task is to retrieve relevant argumentative passages for either compared object or for both and to detect their respective stances with respect to the object they talk about. </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <p> Additionally, classify the stance of the retrieved text passages towards the compared objects in questions. For instance, in the question <i>Who is a better friend, a cat or a dog?</i> the terms <i>cat</i> and <i>dog</i> are the comparison objects. An answer candidate like <i>Cats can be quite affectionate and attentive, and thus are good friends</i> should be classified as pro the <i>cat</i> object, while <i>Cats are less faithful than dogs</i> as supporting the <i>dog</i> object. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/argument-retrieval-for-comparative-questions.html”>Task 2 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.clueweb12.touche-2022-task-2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a comparative topic and a collection of documents, the task is to retrieve relevant argumentative passages for either compared object or for both and to detect their respective stances with respect to the object they talk about. </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <p> Additionally, classify the stance of the retrieved text passages towards the compared objects in questions. For instance, in the question <i>Who is a better friend, a cat or a dog?</i> the terms <i>cat</i> and <i>dog</i> are the comparison objects. An answer candidate like <i>Cats can be quite affectionate and attentive, and thus are good friends</i> should be classified as pro the <i>cat</i> object, while <i>Cats are less faithful than dogs</i> as supporting the <i>dog</i> object. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/argument-retrieval-for-comparative-questions.html”>Task 2 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Dataset irds.clueweb12.touche-2022-task-2

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Decision making processes, be it at the societal or at the personal level, often come to a point where one side challenges the other with a why-question, which is a prompt to justify some stance based on arguments. Since technologies for argument mining are maturing at a rapid pace, also ad-hoc argument retrieval becomes a feasible task in reach. Touché 2022 is the third lab on argument retrieval at CLEF 2022 featuring three tasks. </p> <p> Given a comparative topic and a collection of documents, the task is to retrieve relevant argumentative passages for either compared object or for both and to detect their respective stances with respect to the object they talk about. </p> <p> Documents are judged based on their general topical relevance and for rhetorical quality, i.e., “well-writtenness” of the document: (1) whether the text has a good style of speech (formal language is preferred over informal), (2) whether the text has a proper sentence structure and is easy to read, (3) whether it includes profanity, has typos, and makes use of other detrimental style choices. </p> <p> Additionally, classify the stance of the retrieved text passages towards the compared objects in questions. For instance, in the question <i>Who is a better friend, a cat or a dog?</i> the terms <i>cat</i> and <i>dog</i> are the comparison objects. An answer candidate like <i>Cats can be quite affectionate and attentive, and thus are good friends</i> should be classified as pro the <i>cat</i> object, while <i>Cats are less faithful than dogs</i> as supporting the <i>dog</i> object. </p> <ul> <li><a href=”https://touche.webis.de/clef22/touche22-web/argument-retrieval-for-comparative-questions.html”>Task 2 website</a></li> <li><a href=”https://touche.webis.de/clef22/touche22-web/”>Lab website</a></li> <li><a href=”https://doi.org/10.1007/978-3-030-99739-7_43”>Overview paper</a></li> </ul>

Touché 2022 Task 2: Argument Retrieval for Comparative Questions (Expanded)

<p> Pre-processed version of <a class=”ds-ref”>clueweb12/touche-2022-task-2</a> where each passage has been expanded with queries generated using DocT5Query. </p>

Dataset irds.clueweb12.touche-2022-task-2.expanded-doc-t5-query.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Pre-processed version of <a class=”ds-ref”>clueweb12/touche-2022-task-2</a> where each passage has been expanded with queries generated using DocT5Query. </p>

Dataset irds.clueweb12.touche-2022-task-2.expanded-doc-t5-query.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Pre-processed version of <a class=”ds-ref”>clueweb12/touche-2022-task-2</a> where each passage has been expanded with queries generated using DocT5Query. </p>

Dataset irds.clueweb12.touche-2022-task-2.expanded-doc-t5-query.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Pre-processed version of <a class=”ds-ref”>clueweb12/touche-2022-task-2</a> where each passage has been expanded with queries generated using DocT5Query. </p>

Dataset irds.clueweb12.touche-2022-task-2.expanded-doc-t5-query

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Pre-processed version of <a class=”ds-ref”>clueweb12/touche-2022-task-2</a> where each passage has been expanded with queries generated using DocT5Query. </p>

TREC Arabic

<p> A collection of news articles in Arabic, used for multi-lingual evaluation in TREC 2001 and TREC 2002. </p> <p> Document collection from <a href=”https://catalog.ldc.upenn.edu/LDC2001T55”>LDC2001T55</a>. </p>

Dataset irds.trec-arabic.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A collection of news articles in Arabic, used for multi-lingual evaluation in TREC 2001 and TREC 2002. </p> <p> Document collection from <a href=”https://catalog.ldc.upenn.edu/LDC2001T55”>LDC2001T55</a>. </p>

Dataset irds.trec-arabic.ar2001.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Arabic benchmark from TREC 2001. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec10/papers/clirtrack.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-arabic.ar2001.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Arabic benchmark from TREC 2001. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec10/papers/clirtrack.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-arabic.ar2001

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Arabic benchmark from TREC 2001. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec10/papers/clirtrack.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-arabic.ar2002.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Arabic benchmark from TREC 2002. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/OVERVIEW.gey.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-arabic.ar2002.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Arabic benchmark from TREC 2002. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/OVERVIEW.gey.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-arabic.ar2002

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Arabic benchmark from TREC 2002. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec11/papers/OVERVIEW.gey.ps.gz”>Task Overview Paper</a></li> </ul>

TREC Mandarin

<p> A collection of news articles in Mandarin in Simplified Chinese, used for multi-lingual evaluation in TREC 5 and TREC 6. </p> <p> Document collection from <a href=”https://catalog.ldc.upenn.edu/LDC2000T52”>LDC2000T52</a>. </p>

Dataset irds.trec-mandarin.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A collection of news articles in Mandarin in Simplified Chinese, used for multi-lingual evaluation in TREC 5 and TREC 6. </p> <p> Document collection from <a href=”https://catalog.ldc.upenn.edu/LDC2000T52”>LDC2000T52</a>. </p>

Dataset irds.trec-mandarin.trec5.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Mandarin Chinese benchmark from TREC 5. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec5/papers/multilingual_track.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-mandarin.trec5.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Mandarin Chinese benchmark from TREC 5. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec5/papers/multilingual_track.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-mandarin.trec5

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Mandarin Chinese benchmark from TREC 5. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec5/papers/multilingual_track.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-mandarin.trec6.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Mandarin Chinese benchmark from TREC 6. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec6/papers/csiro.chinese.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-mandarin.trec6.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Mandarin Chinese benchmark from TREC 6. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec6/papers/csiro.chinese.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-mandarin.trec6

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Mandarin Chinese benchmark from TREC 6. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec6/papers/csiro.chinese.ps.gz”>Task Overview Paper</a></li> </ul>

TREC Spanish

<p> A collection of news articles in Spanish, used for multi-lingual evaluation in TREC 3 and TREC 4. </p> <p> Document collection from <a href=”https://catalog.ldc.upenn.edu/LDC2000T51”>LDC2000T51</a>. </p>

Dataset irds.trec-spanish.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A collection of news articles in Spanish, used for multi-lingual evaluation in TREC 3 and TREC 4. </p> <p> Document collection from <a href=”https://catalog.ldc.upenn.edu/LDC2000T51”>LDC2000T51</a>. </p>

Dataset irds.trec-spanish.trec3.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Spanish benchmark from TREC 3. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec3/papers/overview.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-spanish.trec3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Spanish benchmark from TREC 3. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec3/papers/overview.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-spanish.trec3

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Spanish benchmark from TREC 3. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec3/papers/overview.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-spanish.trec4.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Spanish benchmark from TREC 4. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec4/overview.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-spanish.trec4.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Spanish benchmark from TREC 4. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec4/overview.ps.gz”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-spanish.trec4

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Spanish benchmark from TREC 4. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec4/overview.ps.gz”>Task Overview Paper</a></li> </ul>

trec-tot/2023

<p> Corpus for the TREC 2023 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2023.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Corpus for the TREC 2023 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2023.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Train query set for TREC 2023 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2023.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Train query set for TREC 2023 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2023.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Train query set for TREC 2023 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2023.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Dev query set for TREC 2023 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2023.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Dev query set for TREC 2023 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2023.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Dev query set for TREC 2023 tip-of-the-tongue search track. </p>

trec-tot/2024

<p> Corpus for the TREC 2024 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2024.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Corpus for the TREC 2024 tip-of-the-tongue search track. </p>

Dataset irds.trec-tot.2024.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test query set for TREC 2024 tip-of-the-tongue search track. </p>

TripClick

<p> TripClick is a large collection from the <a href=”https://www.tripdatabase.com/”>Trip Database</a>. Relevance is inferred from click signals. </p> <p> A copy of this dataset can be obtained from the Trip Database through the process described <a href=”https://tripdatabase.github.io/tripclick/#getting-the-data”>here</a>. Documents, queries, and qrels require the “TripClick IR Benchmark”; for scoreddocs and docpairs, you will also need to request the “TripClick Training Package for Deep Learning Models”. </p> <ul> <li>Documents: <a href=”https://www.nlm.nih.gov/medline/medline_overview.html”>Medline</a> article titles and abstracts</li> <li>Queries: user queries issued to the <a href=”https://www.tripdatabase.com/”>Trip Database</a></li> <li>Qrels: Inferred from clicks</li> <li><a href=”https://docs.google.com/document/d/1RHVxVnZsPBDDZMDcSvbB8VyNZDl2cn6KpeeSvIu6g_c/edit?usp=sharing”>Dataset request form</a></li> <li><a href=”https://tripdatabase.github.io/tripclick/”>Dataset website</a></li> <li><a href=”https://arxiv.org/abs/2103.07901”>Dataset paper</a></li> </ul>

Dataset irds.tripclick.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> TripClick is a large collection from the <a href=”https://www.tripdatabase.com/”>Trip Database</a>. Relevance is inferred from click signals. </p> <p> A copy of this dataset can be obtained from the Trip Database through the process described <a href=”https://tripdatabase.github.io/tripclick/#getting-the-data”>here</a>. Documents, queries, and qrels require the “TripClick IR Benchmark”; for scoreddocs and docpairs, you will also need to request the “TripClick Training Package for Deep Learning Models”. </p> <ul> <li>Documents: <a href=”https://www.nlm.nih.gov/medline/medline_overview.html”>Medline</a> article titles and abstracts</li> <li>Queries: user queries issued to the <a href=”https://www.tripdatabase.com/”>Trip Database</a></li> <li>Qrels: Inferred from clicks</li> <li><a href=”https://docs.google.com/document/d/1RHVxVnZsPBDDZMDcSvbB8VyNZDl2cn6KpeeSvIu6g_c/edit?usp=sharing”>Dataset request form</a></li> <li><a href=”https://tripdatabase.github.io/tripclick/”>Dataset website</a></li> <li><a href=”https://arxiv.org/abs/2103.07901”>Dataset paper</a></li> </ul>

Dataset irds.tripclick.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/test/head</a>, <a class=”ds-ref”>tripclick/test/torso</a>, and <a class=”ds-ref”>tripclick/test/tail</a>. </p> <p> The scoreddocs are the official BM25 results from Anserini. </p>

Dataset irds.tripclick.test.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Test subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/test/head</a>, <a class=”ds-ref”>tripclick/test/torso</a>, and <a class=”ds-ref”>tripclick/test/tail</a>. </p> <p> The scoreddocs are the official BM25 results from Anserini. </p>

Dataset irds.tripclick.test.head.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.test.head.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.test.tail.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The least frequent queries in the test set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.test.tail.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> The least frequent queries in the test set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.test.torso.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The moderately frequent queries in the test set. This represents 30% of the search engine traffic. </p>

Dataset irds.tripclick.test.torso.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> The moderately frequent queries in the test set. This represents 30% of the search engine traffic. </p>

Dataset irds.tripclick.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/train/head</a>, <a class=”ds-ref”>tripclick/train/torso</a>, and <a class=”ds-ref”>tripclick/train/tail</a>. </p> <p> The dataset provides docpairs in a full text format; we map this text back to the query and doc IDs. A small number of docpairs could not be mapped back, so they are skipped. </p>

Dataset irds.tripclick.train.docpairs

<p> Training subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/train/head</a>, <a class=”ds-ref”>tripclick/train/torso</a>, and <a class=”ds-ref”>tripclick/train/tail</a>. </p> <p> The dataset provides docpairs in a full text format; we map this text back to the query and doc IDs. A small number of docpairs could not be mapped back, so they are skipped. </p>

Dataset irds.tripclick.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/train/head</a>, <a class=”ds-ref”>tripclick/train/torso</a>, and <a class=”ds-ref”>tripclick/train/tail</a>. </p> <p> The dataset provides docpairs in a full text format; we map this text back to the query and doc IDs. A small number of docpairs could not be mapped back, so they are skipped. </p>

Dataset irds.tripclick.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/train/head</a>, <a class=”ds-ref”>tripclick/train/torso</a>, and <a class=”ds-ref”>tripclick/train/tail</a>. </p> <p> The dataset provides docpairs in a full text format; we map this text back to the query and doc IDs. A small number of docpairs could not be mapped back, so they are skipped. </p>

Dataset irds.tripclick.train.head.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The most frequent queries in the train set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.train.head.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The most frequent queries in the train set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.train.head

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The most frequent queries in the train set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.train.head.dctr.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The most frequent queries in the train set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.train.head.dctr.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The most frequent queries in the train set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.train.head.dctr

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The most frequent queries in the train set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.train.hofstaetter-triples.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A version of <a class=”ds-ref”>tripclick/train</a> that replaces the original (noisy) training triples (docpairs) with those sampled from BM25 instead, as suggested by Hofstätter et al (2022). </p> <ul> <li><a href=”https://arxiv.org/pdf/2201.00365.pdf”>Paper</a></li> </ul>

Dataset irds.tripclick.train.hofstaetter-triples.docpairs

<p> A version of <a class=”ds-ref”>tripclick/train</a> that replaces the original (noisy) training triples (docpairs) with those sampled from BM25 instead, as suggested by Hofstätter et al (2022). </p> <ul> <li><a href=”https://arxiv.org/pdf/2201.00365.pdf”>Paper</a></li> </ul>

Dataset irds.tripclick.train.hofstaetter-triples.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A version of <a class=”ds-ref”>tripclick/train</a> that replaces the original (noisy) training triples (docpairs) with those sampled from BM25 instead, as suggested by Hofstätter et al (2022). </p> <ul> <li><a href=”https://arxiv.org/pdf/2201.00365.pdf”>Paper</a></li> </ul>

Dataset irds.tripclick.train.hofstaetter-triples

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A version of <a class=”ds-ref”>tripclick/train</a> that replaces the original (noisy) training triples (docpairs) with those sampled from BM25 instead, as suggested by Hofstätter et al (2022). </p> <ul> <li><a href=”https://arxiv.org/pdf/2201.00365.pdf”>Paper</a></li> </ul>

Dataset irds.tripclick.train.tail.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The least frequent queries in the train set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.train.tail.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The least frequent queries in the train set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.train.tail

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The least frequent queries in the train set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.train.torso.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The moderately frequent queries in the train set. This represents 30% of the search engine traffic. </p>

Dataset irds.tripclick.train.torso.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The moderately frequent queries in the train set. This represents 30% of the search engine traffic. </p>

Dataset irds.tripclick.train.torso

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The moderately frequent queries in the train set. This represents 30% of the search engine traffic. </p>

Dataset irds.tripclick.val.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Validation subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/val/head</a>, <a class=”ds-ref”>tripclick/val/torso</a>, and <a class=”ds-ref”>tripclick/val/tail</a>. </p> <p> The scoreddocs are the official BM25 results from Anserini. </p>

Dataset irds.tripclick.val.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Validation subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/val/head</a>, <a class=”ds-ref”>tripclick/val/torso</a>, and <a class=”ds-ref”>tripclick/val/tail</a>. </p> <p> The scoreddocs are the official BM25 results from Anserini. </p>

Dataset irds.tripclick.val.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Validation subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/val/head</a>, <a class=”ds-ref”>tripclick/val/torso</a>, and <a class=”ds-ref”>tripclick/val/tail</a>. </p> <p> The scoreddocs are the official BM25 results from Anserini. </p>

Dataset irds.tripclick.val

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Validation subset of <a class=”ds-ref”>tripclick</a>, including all queries from <a class=”ds-ref”>tripclick/val/head</a>, <a class=”ds-ref”>tripclick/val/torso</a>, and <a class=”ds-ref”>tripclick/val/tail</a>. </p> <p> The scoreddocs are the official BM25 results from Anserini. </p>

Dataset irds.tripclick.val.head.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.val.head.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.val.head.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.val.head

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.val.head.dctr.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.val.head.dctr.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.val.head.dctr.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.val.head.dctr

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The most frequent queries in the validation set. This represents 20% of the search engine traffic. </p>

Dataset irds.tripclick.val.tail.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The least frequent queries in the validation set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.val.tail.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> The least frequent queries in the validation set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.val.tail.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The least frequent queries in the validation set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.val.tail

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The least frequent queries in the validation set. This represents 50% of the search engine traffic. </p>

Dataset irds.tripclick.val.torso.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The moderately frequent queries in the validation set. This represents 30% of the search engine traffic. </p>

Dataset irds.tripclick.val.torso.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> The moderately frequent queries in the validation set. This represents 30% of the search engine traffic. </p>

Dataset irds.tripclick.val.torso.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The moderately frequent queries in the validation set. This represents 30% of the search engine traffic. </p>

Dataset irds.tripclick.val.torso

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The moderately frequent queries in the validation set. This represents 30% of the search engine traffic. </p>

tripclick/logs

<p> Raw query logs from TripClick. </p> <p> Note that this subset includes a broader set of documents than the main collection, but they only provide the title and URL. </p>

Dataset irds.tripclick.logs.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Raw query logs from TripClick. </p> <p> Note that this subset includes a broader set of documents than the main collection, but they only provide the title and URL. </p>

Tweets 2013 (Internet Archive)

<p> A collection of tweets from a 2-month window achived by the Internet Achive. This collection can be a stand-in document collection for the TREC Microblog 2013-14 tasks. (Even though it is not exactly the same collection, <a href=”https://cs.uwaterloo.ca/~jimmylin/publications/Sequiera_Lin_SIGIR2017.pdf”>Sequiera and Lin</a> show that it it close enough.) </p> <p> This collection is automatically downloaded from the Internet Archive, though download speeds are often slow so it takes some time. ir_datasets constructs a new directory hierarchy during the download process to facilitate fast lookups and slices. </p> <ul> <li>Documents: Tweets</li> <li><a href=”https://cs.uwaterloo.ca/~jimmylin/publications/Sequiera_Lin_SIGIR2017.pdf”>Information about dataset (paper)</a></li> <li><a href=”https://github.com/castorini/Tweets2013-IA”>Information about dataset (repository)</a></li> </ul>

Dataset irds.tweets2013-ia.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A collection of tweets from a 2-month window achived by the Internet Achive. This collection can be a stand-in document collection for the TREC Microblog 2013-14 tasks. (Even though it is not exactly the same collection, <a href=”https://cs.uwaterloo.ca/~jimmylin/publications/Sequiera_Lin_SIGIR2017.pdf”>Sequiera and Lin</a> show that it it close enough.) </p> <p> This collection is automatically downloaded from the Internet Archive, though download speeds are often slow so it takes some time. ir_datasets constructs a new directory hierarchy during the download process to facilitate fast lookups and slices. </p> <ul> <li>Documents: Tweets</li> <li><a href=”https://cs.uwaterloo.ca/~jimmylin/publications/Sequiera_Lin_SIGIR2017.pdf”>Information about dataset (paper)</a></li> <li><a href=”https://github.com/castorini/Tweets2013-IA”>Information about dataset (repository)</a></li> </ul>

Dataset irds.tweets2013-ia.trec-mb-2013.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> TREC Microblog 2013 test collection. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/MB.OVERVIEW.pdf”>Shared Task Paper</a></li> <li><a href=”https://github.com/lintool/twitter-tools/wiki/TREC-2013-Track-Guidelines”>Shared Task Site</a></li> </ul>

Dataset irds.tweets2013-ia.trec-mb-2013.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> TREC Microblog 2013 test collection. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/MB.OVERVIEW.pdf”>Shared Task Paper</a></li> <li><a href=”https://github.com/lintool/twitter-tools/wiki/TREC-2013-Track-Guidelines”>Shared Task Site</a></li> </ul>

Dataset irds.tweets2013-ia.trec-mb-2013

→ datamaestro_text.datasets.irds.data.Adhoc

<p> TREC Microblog 2013 test collection. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec22/papers/MB.OVERVIEW.pdf”>Shared Task Paper</a></li> <li><a href=”https://github.com/lintool/twitter-tools/wiki/TREC-2013-Track-Guidelines”>Shared Task Site</a></li> </ul>

Dataset irds.tweets2013-ia.trec-mb-2014.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> TREC Microblog 2014 test collection. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec23/papers/overview-microblog.pdf”>Shared Task Paper</a></li> <li><a href=”https://github.com/lintool/twitter-tools/wiki/TREC-2014-Track-Guidelines”>Shared Task Site</a></li> </ul>

Dataset irds.tweets2013-ia.trec-mb-2014.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> TREC Microblog 2014 test collection. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec23/papers/overview-microblog.pdf”>Shared Task Paper</a></li> <li><a href=”https://github.com/lintool/twitter-tools/wiki/TREC-2014-Track-Guidelines”>Shared Task Site</a></li> </ul>

Dataset irds.tweets2013-ia.trec-mb-2014

→ datamaestro_text.datasets.irds.data.Adhoc

<p> TREC Microblog 2014 test collection. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec23/papers/overview-microblog.pdf”>Shared Task Paper</a></li> <li><a href=”https://github.com/lintool/twitter-tools/wiki/TREC-2014-Track-Guidelines”>Shared Task Site</a></li> </ul>

Vaswani

<p> A small corpus of roughly 11,000 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language keywords</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/npl/”>Dataset Information</a></li> </ul>

Dataset irds.vaswani.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A small corpus of roughly 11,000 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language keywords</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/npl/”>Dataset Information</a></li> </ul>

Dataset irds.vaswani.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A small corpus of roughly 11,000 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language keywords</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/npl/”>Dataset Information</a></li> </ul>

Dataset irds.vaswani.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A small corpus of roughly 11,000 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language keywords</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/npl/”>Dataset Information</a></li> </ul>

Dataset irds.vaswani

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A small corpus of roughly 11,000 scientific abstracts. </p> <ul> <li>Documents: Scientific abstracts</li> <li>Queries: Natural language keywords</li> <li><a href=”http://ir.dcs.gla.ac.uk/resources/test_collections/npl/”>Dataset Information</a></li> </ul>

wapo/v2

<p> Version 2 of the Washington Post collection, consisting of articles published between 2012-2017. </p> <p> The collection is obtained from NIST by requesting it from NIST <a href=”https://trec.nist.gov/data/wapost/”>here</a>. </p> <p> body contains all body text in plain text format, including paragrphs and multi-media captions. body_paras_html contains only source paragraphs and contains HTML markup. body_media contains images, videos, tweets, and galeries, along with a link to the content and a textual caption. </p> <ul> <li><a href=”https://trec.nist.gov/data/wapost/”>Collection Website</a></li> </ul>

Dataset irds.wapo.v2.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version 2 of the Washington Post collection, consisting of articles published between 2012-2017. </p> <p> The collection is obtained from NIST by requesting it from NIST <a href=”https://trec.nist.gov/data/wapost/”>here</a>. </p> <p> body contains all body text in plain text format, including paragrphs and multi-media captions. body_paras_html contains only source paragraphs and contains HTML markup. body_media contains images, videos, tweets, and galeries, along with a link to the content and a textual caption. </p> <ul> <li><a href=”https://trec.nist.gov/data/wapost/”>Collection Website</a></li> </ul>

Dataset irds.wapo.v2.trec-core-2018.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC Common Core 2018 benchmark. </p> <ul> <li>Queries: TREC-style (keyword, description, narrative)</li> <li>Relevance: Deeply-annotated</li> <li><a href=”https://github.com/trec-core/2018”>Shared Task Website</a></li> <ul>

Dataset irds.wapo.v2.trec-core-2018.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC Common Core 2018 benchmark. </p> <ul> <li>Queries: TREC-style (keyword, description, narrative)</li> <li>Relevance: Deeply-annotated</li> <li><a href=”https://github.com/trec-core/2018”>Shared Task Website</a></li> <ul>

Dataset irds.wapo.v2.trec-core-2018

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC Common Core 2018 benchmark. </p> <ul> <li>Queries: TREC-style (keyword, description, narrative)</li> <li>Relevance: Deeply-annotated</li> <li><a href=”https://github.com/trec-core/2018”>Shared Task Website</a></li> <ul>

Dataset irds.wapo.v2.trec-news-2018.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC News 2018 Background Linking task. The task is to find relevant background information for the provided articles. </p> <ul> <li>Queries: Articles via the doc_id field</li> <li><a href=”http://trec-news.org/”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-News.pdf”>Sared task paper</a></li> <ul>

Dataset irds.wapo.v2.trec-news-2018.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC News 2018 Background Linking task. The task is to find relevant background information for the provided articles. </p> <ul> <li>Queries: Articles via the doc_id field</li> <li><a href=”http://trec-news.org/”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-News.pdf”>Sared task paper</a></li> <ul>

Dataset irds.wapo.v2.trec-news-2018

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC News 2018 Background Linking task. The task is to find relevant background information for the provided articles. </p> <ul> <li>Queries: Articles via the doc_id field</li> <li><a href=”http://trec-news.org/”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec27/papers/Overview-News.pdf”>Sared task paper</a></li> <ul>

Dataset irds.wapo.v2.trec-news-2019.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> The TREC News 2019 Background Linking task. The task is to find relevant background information for the provided articles. </p> <ul> <li>Queries: Articles via the doc_id field</li> <li><a href=”http://trec-news.org/”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.N.pdf”>Sared task paper</a></li> <ul>

Dataset irds.wapo.v2.trec-news-2019.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> The TREC News 2019 Background Linking task. The task is to find relevant background information for the provided articles. </p> <ul> <li>Queries: Articles via the doc_id field</li> <li><a href=”http://trec-news.org/”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.N.pdf”>Sared task paper</a></li> <ul>

Dataset irds.wapo.v2.trec-news-2019

→ datamaestro_text.datasets.irds.data.Adhoc

<p> The TREC News 2019 Background Linking task. The task is to find relevant background information for the provided articles. </p> <ul> <li>Queries: Articles via the doc_id field</li> <li><a href=”http://trec-news.org/”>Shared Task Website</a></li> <li><a href=”https://trec.nist.gov/pubs/trec28/papers/OVERVIEW.N.pdf”>Sared task paper</a></li> <ul>

wapo/v4

Dataset irds.wapo.v4.documents

→ datamaestro_text.datasets.irds.data.Documents

wikiclir/ar

<p> WikiCLIR with Arabic documents. </p>

Dataset irds.wikiclir.ar.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Arabic documents. </p>

Dataset irds.wikiclir.ar.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Arabic documents. </p>

Dataset irds.wikiclir.ar.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Arabic documents. </p>

Dataset irds.wikiclir.ar

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Arabic documents. </p>

wikiclir/ca

<p> WikiCLIR with Catalan documents. </p>

Dataset irds.wikiclir.ca.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Catalan documents. </p>

Dataset irds.wikiclir.ca.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Catalan documents. </p>

Dataset irds.wikiclir.ca.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Catalan documents. </p>

Dataset irds.wikiclir.ca

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Catalan documents. </p>

wikiclir/cs

<p> WikiCLIR with Czech documents. </p>

Dataset irds.wikiclir.cs.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Czech documents. </p>

Dataset irds.wikiclir.cs.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Czech documents. </p>

Dataset irds.wikiclir.cs.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Czech documents. </p>

Dataset irds.wikiclir.cs

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Czech documents. </p>

wikiclir/de

<p> WikiCLIR with German documents. </p>

Dataset irds.wikiclir.de.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with German documents. </p>

Dataset irds.wikiclir.de.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with German documents. </p>

Dataset irds.wikiclir.de.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with German documents. </p>

Dataset irds.wikiclir.de

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with German documents. </p>

wikiclir/en-simple

<p> WikiCLIR with Simple English documents. </p>

Dataset irds.wikiclir.en-simple.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Simple English documents. </p>

Dataset irds.wikiclir.en-simple.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Simple English documents. </p>

Dataset irds.wikiclir.en-simple.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Simple English documents. </p>

Dataset irds.wikiclir.en-simple

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Simple English documents. </p>

wikiclir/es

<p> WikiCLIR with Spanish documents. </p>

Dataset irds.wikiclir.es.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Spanish documents. </p>

Dataset irds.wikiclir.es.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Spanish documents. </p>

Dataset irds.wikiclir.es.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Spanish documents. </p>

Dataset irds.wikiclir.es

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Spanish documents. </p>

wikiclir/fi

<p> WikiCLIR with Finnish documents. </p>

Dataset irds.wikiclir.fi.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Finnish documents. </p>

Dataset irds.wikiclir.fi.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Finnish documents. </p>

Dataset irds.wikiclir.fi.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Finnish documents. </p>

Dataset irds.wikiclir.fi

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Finnish documents. </p>

wikiclir/fr

<p> WikiCLIR with French documents. </p>

Dataset irds.wikiclir.fr.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with French documents. </p>

Dataset irds.wikiclir.fr.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with French documents. </p>

Dataset irds.wikiclir.fr.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with French documents. </p>

Dataset irds.wikiclir.fr

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with French documents. </p>

wikiclir/it

<p> WikiCLIR with Italian documents. </p>

Dataset irds.wikiclir.it.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Italian documents. </p>

Dataset irds.wikiclir.it.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Italian documents. </p>

Dataset irds.wikiclir.it.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Italian documents. </p>

Dataset irds.wikiclir.it

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Italian documents. </p>

wikiclir/ja

<p> WikiCLIR with Japanese documents. </p>

Dataset irds.wikiclir.ja.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Japanese documents. </p>

Dataset irds.wikiclir.ja.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Japanese documents. </p>

Dataset irds.wikiclir.ja.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Japanese documents. </p>

Dataset irds.wikiclir.ja

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Japanese documents. </p>

wikiclir/ko

<p> WikiCLIR with Korean documents. </p>

Dataset irds.wikiclir.ko.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Korean documents. </p>

Dataset irds.wikiclir.ko.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Korean documents. </p>

Dataset irds.wikiclir.ko.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Korean documents. </p>

Dataset irds.wikiclir.ko

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Korean documents. </p>

wikiclir/nl

<p> WikiCLIR with Dutch documents. </p>

Dataset irds.wikiclir.nl.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Dutch documents. </p>

Dataset irds.wikiclir.nl.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Dutch documents. </p>

Dataset irds.wikiclir.nl.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Dutch documents. </p>

Dataset irds.wikiclir.nl

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Dutch documents. </p>

wikiclir/nn

<p> WikiCLIR with Norwegian (Bokmål) documents. </p>

Dataset irds.wikiclir.nn.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Norwegian (Bokmål) documents. </p>

Dataset irds.wikiclir.nn.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Norwegian (Bokmål) documents. </p>

Dataset irds.wikiclir.nn.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Norwegian (Bokmål) documents. </p>

Dataset irds.wikiclir.nn

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Norwegian (Bokmål) documents. </p>

wikiclir/no

<p> WikiCLIR with Norwegian (Nynorsk) documents. </p>

Dataset irds.wikiclir.no.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Norwegian (Nynorsk) documents. </p>

Dataset irds.wikiclir.no.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Norwegian (Nynorsk) documents. </p>

Dataset irds.wikiclir.no.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Norwegian (Nynorsk) documents. </p>

Dataset irds.wikiclir.no

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Norwegian (Nynorsk) documents. </p>

wikiclir/pl

<p> WikiCLIR with Polish documents. </p>

Dataset irds.wikiclir.pl.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Polish documents. </p>

Dataset irds.wikiclir.pl.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Polish documents. </p>

Dataset irds.wikiclir.pl.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Polish documents. </p>

Dataset irds.wikiclir.pl

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Polish documents. </p>

wikiclir/pt

<p> WikiCLIR with Portuguese documents. </p>

Dataset irds.wikiclir.pt.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Portuguese documents. </p>

Dataset irds.wikiclir.pt.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Portuguese documents. </p>

Dataset irds.wikiclir.pt.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Portuguese documents. </p>

Dataset irds.wikiclir.pt

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Portuguese documents. </p>

wikiclir/ro

<p> WikiCLIR with Romanian documents. </p>

Dataset irds.wikiclir.ro.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Romanian documents. </p>

Dataset irds.wikiclir.ro.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Romanian documents. </p>

Dataset irds.wikiclir.ro.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Romanian documents. </p>

Dataset irds.wikiclir.ro

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Romanian documents. </p>

wikiclir/ru

<p> WikiCLIR with Russian documents. </p>

Dataset irds.wikiclir.ru.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Russian documents. </p>

Dataset irds.wikiclir.ru.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Russian documents. </p>

Dataset irds.wikiclir.ru.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Russian documents. </p>

Dataset irds.wikiclir.ru

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Russian documents. </p>

wikiclir/sv

<p> WikiCLIR with Swedish documents. </p>

Dataset irds.wikiclir.sv.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Swedish documents. </p>

Dataset irds.wikiclir.sv.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Swedish documents. </p>

Dataset irds.wikiclir.sv.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Swedish documents. </p>

Dataset irds.wikiclir.sv

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Swedish documents. </p>

wikiclir/sw

<p> WikiCLIR with Swahili documents. </p>

Dataset irds.wikiclir.sw.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Swahili documents. </p>

Dataset irds.wikiclir.sw.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Swahili documents. </p>

Dataset irds.wikiclir.sw.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Swahili documents. </p>

Dataset irds.wikiclir.sw

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Swahili documents. </p>

wikiclir/tl

<p> WikiCLIR with Tagalog documents. </p>

Dataset irds.wikiclir.tl.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Tagalog documents. </p>

Dataset irds.wikiclir.tl.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Tagalog documents. </p>

Dataset irds.wikiclir.tl.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Tagalog documents. </p>

Dataset irds.wikiclir.tl

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Tagalog documents. </p>

wikiclir/tr

<p> WikiCLIR with Turkish documents. </p>

Dataset irds.wikiclir.tr.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Turkish documents. </p>

Dataset irds.wikiclir.tr.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Turkish documents. </p>

Dataset irds.wikiclir.tr.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Turkish documents. </p>

Dataset irds.wikiclir.tr

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Turkish documents. </p>

wikiclir/uk

<p> WikiCLIR with Ukrainian documents. </p>

Dataset irds.wikiclir.uk.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Ukrainian documents. </p>

Dataset irds.wikiclir.uk.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Ukrainian documents. </p>

Dataset irds.wikiclir.uk.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Ukrainian documents. </p>

Dataset irds.wikiclir.uk

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Ukrainian documents. </p>

wikiclir/vi

<p> WikiCLIR with Vietnamese documents. </p>

Dataset irds.wikiclir.vi.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Vietnamese documents. </p>

Dataset irds.wikiclir.vi.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Vietnamese documents. </p>

Dataset irds.wikiclir.vi.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Vietnamese documents. </p>

Dataset irds.wikiclir.vi

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Vietnamese documents. </p>

wikiclir/zh

<p> WikiCLIR with Chinese documents. </p>

Dataset irds.wikiclir.zh.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikiCLIR with Chinese documents. </p>

Dataset irds.wikiclir.zh.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> WikiCLIR with Chinese documents. </p>

Dataset irds.wikiclir.zh.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> WikiCLIR with Chinese documents. </p>

Dataset irds.wikiclir.zh

→ datamaestro_text.datasets.irds.data.Adhoc

<p> WikiCLIR with Chinese documents. </p>

wikir/en1k

<p> A small version of WikIR for English. </p>

Dataset irds.wikir.en1k.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A small version of WikIR for English. </p>

Dataset irds.wikir.en1k.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.test.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Test set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.training.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.training.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Training set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.training.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.training

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.validation.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Validation set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.validation.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Validation set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.validation.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Validation set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en1k.validation

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Validation set of <a class=”ds-ref”>wikir/en1k</a>. Scoreddocs are the provided BM25 run. </p>

wikir/en59k

<p> WikIR for English. </p>

Dataset irds.wikir.en59k.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikIR for English. </p>

Dataset irds.wikir.en59k.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.test.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Test set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.training.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.training.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Training set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.training.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.training

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.validation.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Validation set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.validation.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Validation set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.validation.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Validation set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en59k.validation

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Validation set of <a class=”ds-ref”>wikir/en59k</a>. Scoreddocs are the provided BM25 run. </p>

wikir/en78k

<p> WikIR for English. This is one of the two versions used in <a href=”https://aclanthology.org/2020.lrec-1.237.pdf”>Frej2020Wikir</a>. </p>

Dataset irds.wikir.en78k.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikIR for English. This is one of the two versions used in <a href=”https://aclanthology.org/2020.lrec-1.237.pdf”>Frej2020Wikir</a>. </p>

Dataset irds.wikir.en78k.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.test.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Test set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.training.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.training.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Training set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.training.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.training

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.validation.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Validation set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.validation.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Validation set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.validation.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Validation set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.en78k.validation

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Validation set of <a class=”ds-ref”>wikir/en78k</a>. Scoreddocs are the provided BM25 run. </p>

wikir/ens78k

<p> WikIR for English, using the first sentences of articles as queries. This is one of the two versions used in <a href=”https://aclanthology.org/2020.lrec-1.237.pdf”>Frej2020Wikir</a>. </p>

Dataset irds.wikir.ens78k.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikIR for English, using the first sentences of articles as queries. This is one of the two versions used in <a href=”https://aclanthology.org/2020.lrec-1.237.pdf”>Frej2020Wikir</a>. </p>

Dataset irds.wikir.ens78k.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.test.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Test set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.training.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.training.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Training set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.training.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.training

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.validation.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Validation set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.validation.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Validation set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.validation.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Validation set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.ens78k.validation

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Validation set of <a class=”ds-ref”>wikir/ens78k</a>. Scoreddocs are the provided BM25 run. </p>

wikir/es13k

<p> WikIR for Spanish. </p>

Dataset irds.wikir.es13k.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikIR for Spanish. </p>

Dataset irds.wikir.es13k.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.test.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Test set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.training.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.training.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Training set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.training.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.training

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.validation.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Validation set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.validation.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Validation set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.validation.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Validation set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.es13k.validation

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Validation set of <a class=”ds-ref”>wikir/es13k</a>. Scoreddocs are the provided BM25 run. </p>

wikir/fr14k

<p> WikIR for French. </p>

Dataset irds.wikir.fr14k.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikIR for French. </p>

Dataset irds.wikir.fr14k.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.test.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Test set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.training.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.training.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Training set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.training.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.training

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.validation.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Validation set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.validation.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Validation set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.validation.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Validation set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.fr14k.validation

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Validation set of <a class=”ds-ref”>wikir/fr14k</a>. Scoreddocs are the provided BM25 run. </p>

wikir/it16k

<p> WikIR for Italian. </p>

Dataset irds.wikir.it16k.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> WikIR for Italian. </p>

Dataset irds.wikir.it16k.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.test.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Test set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.training.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.training.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Training set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.training.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.training

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.validation.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Validation set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.validation.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Validation set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.validation.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Validation set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

Dataset irds.wikir.it16k.validation

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Validation set of <a class=”ds-ref”>wikir/it16k</a>. Scoreddocs are the provided BM25 run. </p>

TREC Fair Ranking

<p> The TREC Fair Ranking track evaluates systems according to how well they fairly rank documents. </p> <ul> <li><a href=”https://fair-trec.github.io/”>Website</a></li> </ul>

Dataset irds.trec-fair.2021.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The TREC Fair Ranking track evaluates systems according to how well they fairly rank documents. </p> <ul> <li><a href=”https://fair-trec.github.io/”>Website</a></li> </ul>

Dataset irds.trec-fair.2021.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official TREC Fair Ranking 2021 train set. </p>

Dataset irds.trec-fair.2021.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official TREC Fair Ranking 2021 train set. </p>

Dataset irds.trec-fair.2021.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official TREC Fair Ranking 2021 train set. </p>

Dataset irds.trec-fair.2021.eval.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official TREC Fair Ranking 2021 evaluation set. </p>

Dataset irds.trec-fair.2021.eval.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official TREC Fair Ranking 2021 evaluation set. </p>

Dataset irds.trec-fair.2021.eval

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official TREC Fair Ranking 2021 evaluation set. </p>

trec-fair/2022

<p> The TREC Fair Ranking 2022 track focuses on fairly prioritising Wikimedia articles for editing to provide a fair exposure to articles from different groups. </p> <ul> <li><a href=”https://fair-trec.github.io/”>2022 Track Website</a></li> </ul>

Dataset irds.trec-fair.2022.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The TREC Fair Ranking 2022 track focuses on fairly prioritising Wikimedia articles for editing to provide a fair exposure to articles from different groups. </p> <ul> <li><a href=”https://fair-trec.github.io/”>2022 Track Website</a></li> </ul>

Dataset irds.trec-fair.2022.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official TREC Fair Ranking 2022 train set. </p>

Dataset irds.trec-fair.2022.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official TREC Fair Ranking 2022 train set. </p>

Dataset irds.trec-fair.2022.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official TREC Fair Ranking 2022 train set. </p>

trec-cast/v0

<p> Version 0 of the TREC CAsT corpus. This version uses documents from the Washington Post (version 2), TREC CAR (version 2), and MS MARCO passage (version 1). </p> <p> This corpus was originally meant to be used for evaluation of the 2019 task, but the Washington Post corpus was not included for scoring in the final version due to “an error in the process led to ambiguous document ids,” and Washington Post documents were removed from participating systems. As such, <a class=”ds-ref”>trec-cast/v1</a> (which doesn’t include the Washington Post) should be used for the 2019 version of the task. However, this version still can be used for the training set (<a class=”ds-ref”>trec-cast/v0/train</a>) or for replicating the original submissions to the track (prior to the removal of Washingotn Post documents). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.13624.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-cast.v0.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version 0 of the TREC CAsT corpus. This version uses documents from the Washington Post (version 2), TREC CAR (version 2), and MS MARCO passage (version 1). </p> <p> This corpus was originally meant to be used for evaluation of the 2019 task, but the Washington Post corpus was not included for scoring in the final version due to “an error in the process led to ambiguous document ids,” and Washington Post documents were removed from participating systems. As such, <a class=”ds-ref”>trec-cast/v1</a> (which doesn’t include the Washington Post) should be used for the 2019 version of the task. However, this version still can be used for the training set (<a class=”ds-ref”>trec-cast/v0/train</a>) or for replicating the original submissions to the track (prior to the removal of Washingotn Post documents). </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.13624.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-cast.v0.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Training set provided by TREC CAsT 2019. </p>

Dataset irds.trec-cast.v0.train.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Training set provided by TREC CAsT 2019. </p>

Dataset irds.trec-cast.v0.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Training set provided by TREC CAsT 2019. </p>

Dataset irds.trec-cast.v0.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Training set provided by TREC CAsT 2019. </p>

Dataset irds.trec-cast.v0.train.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>trec-cast/2019/train</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v0.train.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> <a class=”ds-ref”>trec-cast/2019/train</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v0.train.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>trec-cast/2019/train</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v0.train.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>trec-cast/2019/train</a>, but with queries that do not appear in the qrels removed. </p>

trec-cast/v1

<p> Version 1 of the TREC CAsT corpus. This version uses documents from the TREC CAR (version 2) and MS MARCO passage (version 1). This version of the corpus was used for TREC CAsT 2019 and 2020. </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.13624.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-cast.v1.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Version 1 of the TREC CAsT corpus. This version uses documents from the TREC CAR (version 2) and MS MARCO passage (version 1). This version of the corpus was used for TREC CAsT 2019 and 2020. </p> <ul> <li><a href=”https://arxiv.org/pdf/2003.13624.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-cast.v1.2019.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official evaluation set for TREC CAsT 2019. </p>

Dataset irds.trec-cast.v1.2019.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> Official evaluation set for TREC CAsT 2019. </p>

Dataset irds.trec-cast.v1.2019.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official evaluation set for TREC CAsT 2019. </p>

Dataset irds.trec-cast.v1.2019

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official evaluation set for TREC CAsT 2019. </p>

Dataset irds.trec-cast.v1.2019.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>trec-cast/v1/2019</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v1.2019.judged.scoreddocs

→ datamaestro_text.datasets.irds.data.AdhocRun

<p> <a class=”ds-ref”>trec-cast/v1/2019</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v1.2019.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>trec-cast/v1/2019</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v1.2019.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>trec-cast/v1/2019</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v1.2020.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Official evaluation set for TREC CAsT 2020. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec29/papers/OVERVIEW.C.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-cast.v1.2020.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Official evaluation set for TREC CAsT 2020. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec29/papers/OVERVIEW.C.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-cast.v1.2020

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Official evaluation set for TREC CAsT 2020. </p> <ul> <li><a href=”https://trec.nist.gov/pubs/trec29/papers/OVERVIEW.C.pdf”>Task Overview Paper</a></li> </ul>

Dataset irds.trec-cast.v1.2020.judged.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> <a class=”ds-ref”>trec-cast/v1/2020</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v1.2020.judged.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> <a class=”ds-ref”>trec-cast/v1/2020</a>, but with queries that do not appear in the qrels removed. </p>

Dataset irds.trec-cast.v1.2020.judged

→ datamaestro_text.datasets.irds.data.Adhoc

<p> <a class=”ds-ref”>trec-cast/v1/2020</a>, but with queries that do not appear in the qrels removed. </p>

hc4/fa

<p> The Persian collection contains English queries and Persian documents for retrieval. Human and machine translated queries are provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Persian is available. </p>

Dataset irds.hc4.fa.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Persian collection contains English queries and Persian documents for retrieval. Human and machine translated queries are provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Persian is available. </p>

Dataset irds.hc4.fa.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Development split of <a class=”ds-ref”>hc4/fa</a>. </p>

Dataset irds.hc4.fa.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Development split of <a class=”ds-ref”>hc4/fa</a>. </p>

Dataset irds.hc4.fa.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Development split of <a class=”ds-ref”>hc4/fa</a>. </p>

Dataset irds.hc4.fa.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test split of <a class=”ds-ref”>hc4/fa</a>. </p>

Dataset irds.hc4.fa.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test split of <a class=”ds-ref”>hc4/fa</a>. </p>

Dataset irds.hc4.fa.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test split of <a class=”ds-ref”>hc4/fa</a>. </p>

Dataset irds.hc4.fa.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Train split of <a class=”ds-ref”>hc4/fa</a>. </p>

Dataset irds.hc4.fa.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Train split of <a class=”ds-ref”>hc4/fa</a>. </p>

Dataset irds.hc4.fa.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Train split of <a class=”ds-ref”>hc4/fa</a>. </p>

hc4/ru

<p> The Russian collection contains English queries and Russian documents for retrieval. Human and machine translated queries are provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Russian is available. </p>

Dataset irds.hc4.ru.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Russian collection contains English queries and Russian documents for retrieval. Human and machine translated queries are provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Russian is available. </p>

Dataset irds.hc4.ru.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Development split of <a class=”ds-ref”>hc4/ru</a>. </p>

Dataset irds.hc4.ru.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Development split of <a class=”ds-ref”>hc4/ru</a>. </p>

Dataset irds.hc4.ru.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Development split of <a class=”ds-ref”>hc4/ru</a>. </p>

Dataset irds.hc4.ru.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test split of <a class=”ds-ref”>hc4/ru</a>. </p>

Dataset irds.hc4.ru.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test split of <a class=”ds-ref”>hc4/ru</a>. </p>

Dataset irds.hc4.ru.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test split of <a class=”ds-ref”>hc4/ru</a>. </p>

Dataset irds.hc4.ru.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Train split of <a class=”ds-ref”>hc4/ru</a>. </p>

Dataset irds.hc4.ru.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Train split of <a class=”ds-ref”>hc4/ru</a>. </p>

Dataset irds.hc4.ru.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Train split of <a class=”ds-ref”>hc4/ru</a>. </p>

hc4/zh

<p> The Chinese collection contains English queries and Chinese documents for retrieval. Human and machine translated queries are provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Chinese is available. </p>

Dataset irds.hc4.zh.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Chinese collection contains English queries and Chinese documents for retrieval. Human and machine translated queries are provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Chinese is available. </p>

Dataset irds.hc4.zh.dev.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Development split of <a class=”ds-ref”>hc4/zh</a>. </p>

Dataset irds.hc4.zh.dev.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Development split of <a class=”ds-ref”>hc4/zh</a>. </p>

Dataset irds.hc4.zh.dev

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Development split of <a class=”ds-ref”>hc4/zh</a>. </p>

Dataset irds.hc4.zh.test.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Test split of <a class=”ds-ref”>hc4/zh</a>. </p>

Dataset irds.hc4.zh.test.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Test split of <a class=”ds-ref”>hc4/zh</a>. </p>

Dataset irds.hc4.zh.test

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Test split of <a class=”ds-ref”>hc4/zh</a>. </p>

Dataset irds.hc4.zh.train.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Train split of <a class=”ds-ref”>hc4/zh</a>. </p>

Dataset irds.hc4.zh.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Train split of <a class=”ds-ref”>hc4/zh</a>. </p>

Dataset irds.hc4.zh.train

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Train split of <a class=”ds-ref”>hc4/zh</a>. </p>

neuclir/1/fa

<p> The Persian collection contains English queries (to be released) and Persian documents for retrieval. Human and machine translated queries will be provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Persian is available. </p>

Dataset irds.neuclir.1.fa.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Persian collection contains English queries (to be released) and Persian documents for retrieval. Human and machine translated queries will be provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Persian is available. </p>

Dataset irds.neuclir.1.fa.trec-2022.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Topics and assessments for the TREC NeuCLIR 2022 (Persian language CLIR). </p>

Dataset irds.neuclir.1.fa.trec-2022.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Topics and assessments for the TREC NeuCLIR 2022 (Persian language CLIR). </p>

Dataset irds.neuclir.1.fa.trec-2022

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Topics and assessments for the TREC NeuCLIR 2022 (Persian language CLIR). </p>

Dataset irds.neuclir.1.fa.trec-2023.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Topics and assessments for the TREC NeuCLIR 2023 (Persian language CLIR). </p>

Dataset irds.neuclir.1.fa.trec-2023.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Topics and assessments for the TREC NeuCLIR 2023 (Persian language CLIR). </p>

Dataset irds.neuclir.1.fa.trec-2023

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Topics and assessments for the TREC NeuCLIR 2023 (Persian language CLIR). </p>

neuclir/1/fa/hc4-filtered

<p> Subset of the Persian collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/fa/dev</a> and <a class=”ds-ref”>hc4/fa/test</a> sets combined. </p>

Dataset irds.neuclir.1.fa.hc4-filtered.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of the Persian collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/fa/dev</a> and <a class=”ds-ref”>hc4/fa/test</a> sets combined. </p>

Dataset irds.neuclir.1.fa.hc4-filtered.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of the Persian collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/fa/dev</a> and <a class=”ds-ref”>hc4/fa/test</a> sets combined. </p>

Dataset irds.neuclir.1.fa.hc4-filtered.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of the Persian collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/fa/dev</a> and <a class=”ds-ref”>hc4/fa/test</a> sets combined. </p>

Dataset irds.neuclir.1.fa.hc4-filtered

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of the Persian collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/fa/dev</a> and <a class=”ds-ref”>hc4/fa/test</a> sets combined. </p>

neuclir/1/multi

<p> A combined corpus of NeuCLIR v1 including all Persian, Russian, and Chinese documents. </p>

Dataset irds.neuclir.1.multi.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A combined corpus of NeuCLIR v1 including all Persian, Russian, and Chinese documents. </p>

Dataset irds.neuclir.1.multi.trec-2023.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Topics and assessments for the TREC NeuCLIR 2023 multi-language retrieval task. </p>

Dataset irds.neuclir.1.multi.trec-2023.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Topics and assessments for the TREC NeuCLIR 2023 multi-language retrieval task. </p>

Dataset irds.neuclir.1.multi.trec-2023

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Topics and assessments for the TREC NeuCLIR 2023 multi-language retrieval task. </p>

neuclir/1/ru

<p> The Russian collection contains English queries (to be released) and Russian documents for retrieval. Human and machine translated queries will be provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Russian is available. </p>

Dataset irds.neuclir.1.ru.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Russian collection contains English queries (to be released) and Russian documents for retrieval. Human and machine translated queries will be provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Russian is available. </p>

Dataset irds.neuclir.1.ru.trec-2022.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Topics and assessments for the TREC NeuCLIR 2022 (Russian language CLIR). </p>

Dataset irds.neuclir.1.ru.trec-2022.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Topics and assessments for the TREC NeuCLIR 2022 (Russian language CLIR). </p>

Dataset irds.neuclir.1.ru.trec-2022

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Topics and assessments for the TREC NeuCLIR 2022 (Russian language CLIR). </p>

Dataset irds.neuclir.1.ru.trec-2023.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Topics and assessments for the TREC NeuCLIR 2023 (Russian language CLIR). </p>

Dataset irds.neuclir.1.ru.trec-2023.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Topics and assessments for the TREC NeuCLIR 2023 (Russian language CLIR). </p>

Dataset irds.neuclir.1.ru.trec-2023

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Topics and assessments for the TREC NeuCLIR 2023 (Russian language CLIR). </p>

neuclir/1/ru/hc4-filtered

<p> Subset of the Russian collection that intersect with HC4. The 54 queries are the <a class=”ds-ref”>hc4/ru/dev</a> and <a class=”ds-ref”>hc4/ru/test</a> sets combined. </p>

Dataset irds.neuclir.1.ru.hc4-filtered.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of the Russian collection that intersect with HC4. The 54 queries are the <a class=”ds-ref”>hc4/ru/dev</a> and <a class=”ds-ref”>hc4/ru/test</a> sets combined. </p>

Dataset irds.neuclir.1.ru.hc4-filtered.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of the Russian collection that intersect with HC4. The 54 queries are the <a class=”ds-ref”>hc4/ru/dev</a> and <a class=”ds-ref”>hc4/ru/test</a> sets combined. </p>

Dataset irds.neuclir.1.ru.hc4-filtered.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of the Russian collection that intersect with HC4. The 54 queries are the <a class=”ds-ref”>hc4/ru/dev</a> and <a class=”ds-ref”>hc4/ru/test</a> sets combined. </p>

Dataset irds.neuclir.1.ru.hc4-filtered

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of the Russian collection that intersect with HC4. The 54 queries are the <a class=”ds-ref”>hc4/ru/dev</a> and <a class=”ds-ref”>hc4/ru/test</a> sets combined. </p>

neuclir/1/zh

<p> The Chinese collection contains English queries (to be released) and Chinese documents for retrieval. Human and machine translated queries will be provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Chinese is available. </p>

Dataset irds.neuclir.1.zh.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> The Chinese collection contains English queries (to be released) and Chinese documents for retrieval. Human and machine translated queries will be provided in the query object for running monolingual retrieval or cross-language retrival assuming the machine query tranlstion into Chinese is available. </p>

Dataset irds.neuclir.1.zh.trec-2022.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Topics and assessments for the TREC NeuCLIR 2022 (Chinese language CLIR). </p>

Dataset irds.neuclir.1.zh.trec-2022.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Topics and assessments for the TREC NeuCLIR 2022 (Chinese language CLIR). </p>

Dataset irds.neuclir.1.zh.trec-2022

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Topics and assessments for the TREC NeuCLIR 2022 (Chinese language CLIR). </p>

Dataset irds.neuclir.1.zh.trec-2023.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Topics and assessments for the TREC NeuCLIR 2023 (Chinese language CLIR). </p>

Dataset irds.neuclir.1.zh.trec-2023.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Topics and assessments for the TREC NeuCLIR 2023 (Chinese language CLIR). </p>

Dataset irds.neuclir.1.zh.trec-2023

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Topics and assessments for the TREC NeuCLIR 2023 (Chinese language CLIR). </p>

neuclir/1/zh/hc4-filtered

<p> Subset of the Chinse collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/zh/dev</a> and <a class=”ds-ref”>hc4/zh/test</a> sets combined. </p>

Dataset irds.neuclir.1.zh.hc4-filtered.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> Subset of the Chinse collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/zh/dev</a> and <a class=”ds-ref”>hc4/zh/test</a> sets combined. </p>

Dataset irds.neuclir.1.zh.hc4-filtered.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> Subset of the Chinse collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/zh/dev</a> and <a class=”ds-ref”>hc4/zh/test</a> sets combined. </p>

Dataset irds.neuclir.1.zh.hc4-filtered.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> Subset of the Chinse collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/zh/dev</a> and <a class=”ds-ref”>hc4/zh/test</a> sets combined. </p>

Dataset irds.neuclir.1.zh.hc4-filtered

→ datamaestro_text.datasets.irds.data.Adhoc

<p> Subset of the Chinse collection that intersect with HC4. The 60 queries are the <a class=”ds-ref”>hc4/zh/dev</a> and <a class=”ds-ref”>hc4/zh/test</a> sets combined. </p>

SARA

<p> A set of sensitivity-aware relevance assessments. More information is avaliable here: <p>

<ul> <li><a href=”https://github.com/JackMcKechnie/SARA-A-Collection-of-Sensitivity-Aware-Relevance-Assessments”>SARA</a></li> </ul>

Dataset irds.sara.documents

→ datamaestro_text.datasets.irds.data.Documents

<p> A set of sensitivity-aware relevance assessments. More information is avaliable here: <p>

<ul> <li><a href=”https://github.com/JackMcKechnie/SARA-A-Collection-of-Sensitivity-Aware-Relevance-Assessments”>SARA</a></li> </ul>

Dataset irds.sara.queries

→ datamaestro_text.datasets.irds.data.Topics

<p> A set of sensitivity-aware relevance assessments. More information is avaliable here: <p>

<ul> <li><a href=”https://github.com/JackMcKechnie/SARA-A-Collection-of-Sensitivity-Aware-Relevance-Assessments”>SARA</a></li> </ul>

Dataset irds.sara.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

<p> A set of sensitivity-aware relevance assessments. More information is avaliable here: <p>

<ul> <li><a href=”https://github.com/JackMcKechnie/SARA-A-Collection-of-Sensitivity-Aware-Relevance-Assessments”>SARA</a></li> </ul>

Dataset irds.sara

→ datamaestro_text.datasets.irds.data.Adhoc

<p> A set of sensitivity-aware relevance assessments. More information is avaliable here: <p>

<ul> <li><a href=”https://github.com/JackMcKechnie/SARA-A-Collection-of-Sensitivity-Aware-Relevance-Assessments”>SARA</a></li> </ul>

trec-tot/2025

Dataset irds.trec-tot.2025.documents

→ datamaestro_text.datasets.irds.data.Documents

trec-tot/2025/train

Dataset irds.trec-tot.2025.train.documents

→ datamaestro_text.datasets.irds.data.Documents

Dataset irds.trec-tot.2025.train.queries

→ datamaestro_text.datasets.irds.data.Topics

Dataset irds.trec-tot.2025.train.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

Dataset irds.trec-tot.2025.train

→ datamaestro_text.datasets.irds.data.Adhoc

trec-tot/2025/dev1

Dataset irds.trec-tot.2025.dev1.documents

→ datamaestro_text.datasets.irds.data.Documents

Dataset irds.trec-tot.2025.dev1.queries

→ datamaestro_text.datasets.irds.data.Topics

Dataset irds.trec-tot.2025.dev1.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

Dataset irds.trec-tot.2025.dev1

→ datamaestro_text.datasets.irds.data.Adhoc

trec-tot/2025/dev2

Dataset irds.trec-tot.2025.dev2.documents

→ datamaestro_text.datasets.irds.data.Documents

Dataset irds.trec-tot.2025.dev2.queries

→ datamaestro_text.datasets.irds.data.Topics

Dataset irds.trec-tot.2025.dev2.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

Dataset irds.trec-tot.2025.dev2

→ datamaestro_text.datasets.irds.data.Adhoc

trec-tot/2025/dev3

Dataset irds.trec-tot.2025.dev3.documents

→ datamaestro_text.datasets.irds.data.Documents

Dataset irds.trec-tot.2025.dev3.queries

→ datamaestro_text.datasets.irds.data.Topics

Dataset irds.trec-tot.2025.dev3.qrels

→ datamaestro_text.datasets.irds.data.AdhocAssessments

Dataset irds.trec-tot.2025.dev3

→ datamaestro_text.datasets.irds.data.Adhoc