ir_datasets: GOV2To use this dataset, you need a copy of GOV2, provided by the University of Glasgow.
Your organization may already have a copy. If this is the case, you may only need to complete a new "Individual Argeement". Otherwise, your organization will need to file the "Organizational agreement" and pay a fee to UoG to get a copy. The data are provided as hard drives that are shipped to you.
Once you have the data, ir_datasets will need the GOV2_data directory.
ir_datasets expects the above directory to be copied/linked under ~/.ir_datasets/gov/corpus.
GOV2 web document collection. Used for the TREC Terabyte Track.
The dataset is obtained for a fee from UoG, and is shipped as a hard drive. More information is provided here.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
TREC 2007 Million Query track.
Language: multiple/other/unknown
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-mq-2007")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-mq-2007 queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-mq-2007")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-mq-2007 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
| 2 | Highly Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-mq-2007")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, method, iprob>
You can find more details about the Python API here.
ir_datasets export gov2/trec-mq-2007 qrels --format tsv
[query_id] [doc_id] [relevance] [method] [iprob]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Allen2007MQ, title={Million Query Track 2007 Overview}, author={James Allan and Ben Carterette and Javed A. Aslam and Virgil Pavlu and Blagovest Dachev and Evangelos Kanoulas}, booktitle={TREC}, year={2007} }TREC 2008 Million Query track.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-mq-2008")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-mq-2008 queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-mq-2008")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-mq-2008 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
| 2 | Highly Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-mq-2008")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, method, iprob>
You can find more details about the Python API here.
ir_datasets export gov2/trec-mq-2008 qrels --format tsv
[query_id] [doc_id] [relevance] [method] [iprob]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Allen2008MQ, title={Million Query Track 2008 Overview}, author={James Allan and Javed A. Aslam and Ben Carterette and Virgil Pavlu and Evangelos Kanoulas}, booktitle={TREC}, year={2008} }The TREC Terabyte Track 2004 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2004")
for query in dataset.queries_iter():
query # namedtuple<query_id, title, description, narrative>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2004 queries
[query_id] [title] [description] [narrative]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2004")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2004 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
| 2 | Highly Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2004")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2004 qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Clarke2004TrecTerabyte, title={Overview of the TREC 2004 Terabyte Track}, author={Charles Clarke and Nick Craswell and Ian Soboroff}, booktitle={TREC}, year={2004} }The TREC Terabyte Track 2005 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005")
for query in dataset.queries_iter():
query # namedtuple<query_id, title, description, narrative>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005 queries
[query_id] [title] [description] [narrative]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
| 2 | Highly Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005 qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Clarke2005TrecTerabyte, title={The TREC 2005 Terabyte Track}, author={Charles L. A. Clark and Falk Scholer and Ian Soboroff}, booktitle={TREC}, year={2005} }The TREC Terabyte Track 2005 efficiency ranking benchmark. Contains 50,000 queries from a search engine, including the 50 topics from gov2/trec-tb-2005. Only the 50 topics have judgments.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005/efficiency")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005/efficiency queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005/efficiency")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005/efficiency docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
| 2 | Highly Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005/efficiency")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005/efficiency qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Clarke2005TrecTerabyte, title={The TREC 2005 Terabyte Track}, author={Charles L. A. Clark and Falk Scholer and Ian Soboroff}, booktitle={TREC}, year={2005} }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.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005/named-page")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005/named-page queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005/named-page")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005/named-page docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2005/named-page")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2005/named-page qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Clarke2005TrecTerabyte, title={The TREC 2005 Terabyte Track}, author={Charles L. A. Clark and Falk Scholer and Ian Soboroff}, booktitle={TREC}, year={2005} }The TREC Terabyte Track 2006 ad-hoc ranking benchmark. Contains 50 queries with deep relevance judgments.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006")
for query in dataset.queries_iter():
query # namedtuple<query_id, title, description, narrative>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006 queries
[query_id] [title] [description] [narrative]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
| 2 | Highly Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006 qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Buttcher2006TrecTerabyte, title={The TREC 2006 Terabyte Track}, author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff}, booktitle={TREC}, year={2006} }The TREC Terabyte Track 2006 efficiency ranking benchmark. Contains 100,000 queries from a search engine, including the 50 topics from gov2/trec-tb-2006. Only the 50 topics have judgments.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
| 2 | Highly Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Buttcher2006TrecTerabyte, title={The TREC 2006 Terabyte Track}, author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff}, booktitle={TREC}, year={2006} }Small stream from gov2/trec-tb-2006/efficiency, with 10,000 queries.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/10k")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/10k queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/10k")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/10k docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Buttcher2006TrecTerabyte, title={The TREC 2006 Terabyte Track}, author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff}, booktitle={TREC}, year={2006} }Stream 1 of gov2/trec-tb-2006/efficiency (25,000 queries).
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream1")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream1 queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream1")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream1 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Buttcher2006TrecTerabyte, title={The TREC 2006 Terabyte Track}, author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff}, booktitle={TREC}, year={2006} }Stream 2 of gov2/trec-tb-2006/efficiency (25,000 queries).
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream2")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream2 queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream2")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream2 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Buttcher2006TrecTerabyte, title={The TREC 2006 Terabyte Track}, author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff}, booktitle={TREC}, year={2006} }Stream 3 of gov2/trec-tb-2006/efficiency (25,000 queries).
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream3")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream3 queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream3")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream3 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
| 2 | Highly Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream3")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream3 qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Buttcher2006TrecTerabyte, title={The TREC 2006 Terabyte Track}, author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff}, booktitle={TREC}, year={2006} }Stream 4 of gov2/trec-tb-2006/efficiency (25,000 queries).
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream4")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream4 queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/efficiency/stream4")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/efficiency/stream4 docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Buttcher2006TrecTerabyte, title={The TREC 2006 Terabyte Track}, author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff}, booktitle={TREC}, year={2006} }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.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/named-page")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/named-page queries
[query_id] [text]
...
You can find more details about the CLI here.
No example available for PyTerrier
Inherits docs from gov2
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/named-page")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, url, http_headers, body, body_content_type>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/named-page docs
[doc_id] [url] [http_headers] [body] [body_content_type]
...
You can find more details about the CLI here.
No example available for PyTerrier
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | Not Relevant |
| 1 | Relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("gov2/trec-tb-2006/named-page")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export gov2/trec-tb-2006/named-page qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
No example available for PyTerrier
Bibtex:
@inproceedings{Buttcher2006TrecTerabyte, title={The TREC 2006 Terabyte Track}, author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff}, booktitle={TREC}, year={2006} }