nthakur commited on
Commit
5c938c5
·
1 Parent(s): 9e6cd3a

Convert nfcorpus dataset to Parquet (#6)

Browse files

- Convert nfcorpus dataset to Parquet (d98637d5f897d400f4878b61ec381bee828dde94)
- Align README with approved BEIR template (2bd517213dba6a15ee60c90195f0123612d09ddf)

README.md CHANGED
@@ -45,10 +45,10 @@ dataset_info:
45
  dtype: string
46
  splits:
47
  - name: corpus
48
- num_bytes: 5856698
49
  num_examples: 3633
50
- download_size: 3193804
51
- dataset_size: 5856698
52
  - config_name: queries
53
  features:
54
  - name: _id
@@ -59,49 +59,25 @@ dataset_info:
59
  dtype: string
60
  splits:
61
  - name: queries
62
- num_bytes: 141303
63
  num_examples: 3237
64
- download_size: 83904
65
- dataset_size: 141303
66
  ---
67
 
68
  # Dataset Card for BEIR Benchmark
69
 
70
- ## Table of Contents
71
- - [Dataset Description](#dataset-description)
72
- - [Dataset Summary](#dataset-summary)
73
- - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
74
- - [Languages](#languages)
75
- - [Dataset Structure](#dataset-structure)
76
- - [Data Instances](#data-instances)
77
- - [Data Fields](#data-fields)
78
- - [Data Splits](#data-splits)
79
- - [Dataset Creation](#dataset-creation)
80
- - [Curation Rationale](#curation-rationale)
81
- - [Source Data](#source-data)
82
- - [Annotations](#annotations)
83
- - [Personal and Sensitive Information](#personal-and-sensitive-information)
84
- - [Considerations for Using the Data](#considerations-for-using-the-data)
85
- - [Social Impact of Dataset](#social-impact-of-dataset)
86
- - [Discussion of Biases](#discussion-of-biases)
87
- - [Other Known Limitations](#other-known-limitations)
88
- - [Additional Information](#additional-information)
89
- - [Dataset Curators](#dataset-curators)
90
- - [Licensing Information](#licensing-information)
91
- - [Citation Information](#citation-information)
92
- - [Contributions](#contributions)
93
-
94
  ## Dataset Description
95
 
96
- - **Homepage:** https://github.com/UKPLab/beir
97
- - **Repository:** https://github.com/UKPLab/beir
98
  - **Paper:** https://openreview.net/forum?id=wCu6T5xFjeJ
99
  - **Leaderboard:** https://docs.google.com/spreadsheets/d/1L8aACyPaXrL8iEelJLGqlMqXKPX2oSP_R10pZoy77Ns
100
  - **Point of Contact:** nandan.thakur@uwaterloo.ca
101
 
102
  ### Dataset Summary
103
 
104
- BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks:
105
 
106
  - Fact-checking: [FEVER](http://fever.ai), [Climate-FEVER](http://climatefever.ai), [SciFact](https://github.com/allenai/scifact)
107
  - Question-Answering: [NQ](https://ai.google.com/research/NaturalQuestions), [HotpotQA](https://hotpotqa.github.io), [FiQA-2018](https://sites.google.com/view/fiqa/)
@@ -113,18 +89,7 @@ BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets r
113
  - Tweet Retrieval: [Signal-1M](https://research.signal-ai.com/datasets/signal1m-tweetir.html)
114
  - Entity Retrieval: [DBPedia](https://github.com/iai-group/DBpedia-Entity/)
115
 
116
- All these datasets have been preprocessed and can be used for your experiments.
117
-
118
-
119
- ```python
120
-
121
- ```
122
-
123
- ### Supported Tasks and Leaderboards
124
-
125
- The dataset supports a leaderboard that evaluates models against task-specific metrics such as F1 or EM, as well as their ability to retrieve supporting information from Wikipedia.
126
-
127
- The current best performing models can be found [here](https://eval.ai/web/challenges/challenge-page/689/leaderboard/).
128
 
129
  ### Languages
130
 
@@ -132,19 +97,25 @@ All tasks are in English (`en`).
132
 
133
  ## Dataset Structure
134
 
135
- All BEIR datasets must contain a corpus, queries and qrels (relevance judgments file). They must be in the following format:
136
- - `corpus` file: a `.jsonl` file (jsonlines) that contains a list of dictionaries, each with three fields `_id` with unique document identifier, `title` with document title (optional) and `text` with document paragraph or passage. For example: `{"_id": "doc1", "title": "Albert Einstein", "text": "Albert Einstein was a German-born...."}`
137
- - `queries` file: a `.jsonl` file (jsonlines) that contains a list of dictionaries, each with two fields `_id` with unique query identifier and `text` with query text. For example: `{"_id": "q1", "text": "Who developed the mass-energy equivalence formula?"}`
138
- - `qrels` file: a `.tsv` file (tab-seperated) that contains three columns, i.e. the `query-id`, `corpus-id` and `score` in this order. Keep 1st row as header. For example: `q1 doc1 1`
 
 
 
 
 
 
139
 
140
  ### Data Instances
141
 
142
- A high level example of any beir dataset:
143
 
144
  ```python
145
  corpus = {
146
  "doc1" : {
147
- "title": "Albert Einstein",
148
  "text": "Albert Einstein was a German-born theoretical physicist. who developed the theory of relativity, \
149
  one of the two pillars of modern physics (alongside quantum mechanics). His work is also known for \
150
  its influence on the philosophy of science. He is best known to the general public for his mass–energy \
@@ -171,111 +142,42 @@ qrels = {
171
  }
172
  ```
173
 
174
- ### Data Fields
175
-
176
- Examples from all configurations have the following features:
177
-
178
- ### Corpus
179
- - `corpus`: a `dict` feature representing the document title and passage text, made up of:
180
- - `_id`: a `string` feature representing the unique document id
181
- - `title`: a `string` feature, denoting the title of the document.
182
- - `text`: a `string` feature, denoting the text of the document.
183
-
184
- ### Queries
185
- - `queries`: a `dict` feature representing the query, made up of:
186
- - `_id`: a `string` feature representing the unique query id
187
- - `text`: a `string` feature, denoting the text of the query.
188
-
189
- ### Qrels
190
- - `qrels`: a `dict` feature representing the query document relevance judgements, made up of:
191
- - `_id`: a `string` feature representing the query id
192
- - `_id`: a `string` feature, denoting the document id.
193
- - `score`: a `int32` feature, denoting the relevance judgement between query and document.
194
-
195
-
196
- ### Data Splits
197
-
198
- | Dataset | Website| BEIR-Name | Type | Queries | Corpus | Rel D/Q | Down-load | md5 |
199
- | -------- | -----| ---------| --------- | ----------- | ---------| ---------| :----------: | :------:|
200
- | MSMARCO | [Homepage](https://microsoft.github.io/msmarco/)| ``msmarco`` | ``train``<br>``dev``<br>``test``| 6,980 | 8.84M | 1.1 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/msmarco.zip) | ``444067daf65d982533ea17ebd59501e4`` |
201
- | TREC-COVID | [Homepage](https://ir.nist.gov/covidSubmit/index.html)| ``trec-covid``| ``test``| 50| 171K| 493.5 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/trec-covid.zip) | ``ce62140cb23feb9becf6270d0d1fe6d1`` |
202
- | NFCorpus | [Homepage](https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/) | ``nfcorpus`` | ``train``<br>``dev``<br>``test``| 323 | 3.6K | 38.2 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/nfcorpus.zip) | ``a89dba18a62ef92f7d323ec890a0d38d`` |
203
- | BioASQ | [Homepage](http://bioasq.org) | ``bioasq``| ``train``<br>``test`` | 500 | 14.91M | 8.05 | No | [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#2-bioasq) |
204
- | NQ | [Homepage](https://ai.google.com/research/NaturalQuestions) | ``nq``| ``train``<br>``test``| 3,452 | 2.68M | 1.2 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/nq.zip) | ``d4d3d2e48787a744b6f6e691ff534307`` |
205
- | HotpotQA | [Homepage](https://hotpotqa.github.io) | ``hotpotqa``| ``train``<br>``dev``<br>``test``| 7,405 | 5.23M | 2.0 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/hotpotqa.zip) | ``f412724f78b0d91183a0e86805e16114`` |
206
- | FiQA-2018 | [Homepage](https://sites.google.com/view/fiqa/) | ``fiqa`` | ``train``<br>``dev``<br>``test``| 648 | 57K | 2.6 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/fiqa.zip) | ``17918ed23cd04fb15047f73e6c3bd9d9`` |
207
- | Signal-1M(RT) | [Homepage](https://research.signal-ai.com/datasets/signal1m-tweetir.html)| ``signal1m`` | ``test``| 97 | 2.86M | 19.6 | No | [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#4-signal-1m) |
208
- | TREC-NEWS | [Homepage](https://trec.nist.gov/data/news2019.html) | ``trec-news`` | ``test``| 57 | 595K | 19.6 | No | [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#1-trec-news) |
209
- | ArguAna | [Homepage](http://argumentation.bplaced.net/arguana/data) | ``arguana``| ``test`` | 1,406 | 8.67K | 1.0 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/arguana.zip) | ``8ad3e3c2a5867cdced806d6503f29b99`` |
210
- | Touche-2020| [Homepage](https://webis.de/events/touche-20/shared-task-1.html) | ``webis-touche2020``| ``test``| 49 | 382K | 19.0 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/webis-touche2020.zip) | ``46f650ba5a527fc69e0a6521c5a23563`` |
211
- | CQADupstack| [Homepage](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/) | ``cqadupstack``| ``test``| 13,145 | 457K | 1.4 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/cqadupstack.zip) | ``4e41456d7df8ee7760a7f866133bda78`` |
212
- | Quora| [Homepage](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs) | ``quora``| ``dev``<br>``test``| 10,000 | 523K | 1.6 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/quora.zip) | ``18fb154900ba42a600f84b839c173167`` |
213
- | DBPedia | [Homepage](https://github.com/iai-group/DBpedia-Entity/) | ``dbpedia-entity``| ``dev``<br>``test``| 400 | 4.63M | 38.2 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/dbpedia-entity.zip) | ``c2a39eb420a3164af735795df012ac2c`` |
214
- | SCIDOCS| [Homepage](https://allenai.org/data/scidocs) | ``scidocs``| ``test``| 1,000 | 25K | 4.9 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/scidocs.zip) | ``38121350fc3a4d2f48850f6aff52e4a9`` |
215
- | FEVER | [Homepage](http://fever.ai) | ``fever``| ``train``<br>``dev``<br>``test``| 6,666 | 5.42M | 1.2| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/fever.zip) | ``5a818580227bfb4b35bb6fa46d9b6c03`` |
216
- | Climate-FEVER| [Homepage](http://climatefever.ai) | ``climate-fever``|``test``| 1,535 | 5.42M | 3.0 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/climate-fever.zip) | ``8b66f0a9126c521bae2bde127b4dc99d`` |
217
- | SciFact| [Homepage](https://github.com/allenai/scifact) | ``scifact``| ``train``<br>``test``| 300 | 5K | 1.1 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/scifact.zip) | ``5f7d1de60b170fc8027bb7898e2efca1`` |
218
- | Robust04 | [Homepage](https://trec.nist.gov/data/robust/04.guidelines.html) | ``robust04``| ``test``| 249 | 528K | 69.9 | No | [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#3-robust04) |
219
-
220
-
221
- ## Dataset Creation
222
-
223
- ### Curation Rationale
224
-
225
- [Needs More Information]
226
-
227
- ### Source Data
228
-
229
- #### Initial Data Collection and Normalization
230
-
231
- [Needs More Information]
232
-
233
- #### Who are the source language producers?
234
-
235
- [Needs More Information]
236
-
237
- ### Annotations
238
-
239
- #### Annotation process
240
-
241
- [Needs More Information]
242
-
243
- #### Who are the annotators?
244
-
245
- [Needs More Information]
246
-
247
- ### Personal and Sensitive Information
248
-
249
- [Needs More Information]
250
-
251
- ## Considerations for Using the Data
252
-
253
- ### Social Impact of Dataset
254
-
255
- [Needs More Information]
256
-
257
- ### Discussion of Biases
258
-
259
- [Needs More Information]
260
-
261
- ### Other Known Limitations
262
-
263
- [Needs More Information]
264
-
265
- ## Additional Information
266
-
267
- ### Dataset Curators
268
-
269
- [Needs More Information]
270
-
271
- ### Licensing Information
272
-
273
- [Needs More Information]
274
-
275
- ### Citation Information
276
-
277
- Cite as:
278
- ```
279
  @inproceedings{
280
  thakur2021beir,
281
  title={{BEIR}: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models},
@@ -285,7 +187,3 @@ year={2021},
285
  url={https://openreview.net/forum?id=wCu6T5xFjeJ}
286
  }
287
  ```
288
-
289
- ### Contributions
290
-
291
- Thanks to [@Nthakur20](https://github.com/Nthakur20) for adding this dataset.
 
45
  dtype: string
46
  splits:
47
  - name: corpus
48
+ num_bytes: 3157570
49
  num_examples: 3633
50
+ download_size: 3157570
51
+ dataset_size: 3157570
52
  - config_name: queries
53
  features:
54
  - name: _id
 
59
  dtype: string
60
  splits:
61
  - name: queries
62
+ num_bytes: 80929
63
  num_examples: 3237
64
+ download_size: 80929
65
+ dataset_size: 80929
66
  ---
67
 
68
  # Dataset Card for BEIR Benchmark
69
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
70
  ## Dataset Description
71
 
72
+ - **Homepage:** https://beir.ai
73
+ - **Repository:** https://beir.ai
74
  - **Paper:** https://openreview.net/forum?id=wCu6T5xFjeJ
75
  - **Leaderboard:** https://docs.google.com/spreadsheets/d/1L8aACyPaXrL8iEelJLGqlMqXKPX2oSP_R10pZoy77Ns
76
  - **Point of Contact:** nandan.thakur@uwaterloo.ca
77
 
78
  ### Dataset Summary
79
 
80
+ BEIR is a heterogeneous benchmark built from 18 diverse datasets representing 9 information retrieval tasks.
81
 
82
  - Fact-checking: [FEVER](http://fever.ai), [Climate-FEVER](http://climatefever.ai), [SciFact](https://github.com/allenai/scifact)
83
  - Question-Answering: [NQ](https://ai.google.com/research/NaturalQuestions), [HotpotQA](https://hotpotqa.github.io), [FiQA-2018](https://sites.google.com/view/fiqa/)
 
89
  - Tweet Retrieval: [Signal-1M](https://research.signal-ai.com/datasets/signal1m-tweetir.html)
90
  - Entity Retrieval: [DBPedia](https://github.com/iai-group/DBpedia-Entity/)
91
 
92
+ > **This `nfcorpus` subset is the Argument Retrieval task within BEIR.**
 
 
 
 
 
 
 
 
 
 
 
93
 
94
  ### Languages
95
 
 
97
 
98
  ## Dataset Structure
99
 
100
+ This dataset uses the standard BEIR retrieval layout and includes:
101
+
102
+ - `corpus`: one row per document with `_id`, `title`, `text`
103
+ - `queries`: one row per query with `_id`, `title`, `text`
104
+
105
+ ### Data Fields
106
+
107
+ - `_id` (`string`): unique identifier
108
+ - `title` (`string`): title (empty string when unavailable)
109
+ - `text` (`string`): document/query text
110
 
111
  ### Data Instances
112
 
113
+ A high level example of any BEIR dataset:
114
 
115
  ```python
116
  corpus = {
117
  "doc1" : {
118
+ "title": "Albert Einstein",
119
  "text": "Albert Einstein was a German-born theoretical physicist. who developed the theory of relativity, \
120
  one of the two pillars of modern physics (alongside quantum mechanics). His work is also known for \
121
  its influence on the philosophy of science. He is best known to the general public for his mass–energy \
 
142
  }
143
  ```
144
 
145
+ ### NFCorpus Data Splits
146
+
147
+ | Subset | Split | Rows |
148
+ | --- | --- | ---: |
149
+ | corpus | corpus | 3,633 |
150
+ | queries | queries | 3,237 |
151
+
152
+ ### BEIR Direct Download
153
+
154
+ You can also download BEIR datasets directly (without loading through Hugging Face datasets) using the links below.
155
+
156
+ | Dataset | Website | BEIR-Name | Type | Queries | Corpus | Rel D/Q | Down-load | md5 |
157
+ | --- | --- | --- | --- | ---: | ---: | ---: | --- | --- |
158
+ | MSMARCO | [Homepage](https://microsoft.github.io/msmarco/) | `msmarco` | `train` `dev` `test` | 6,980 | 8.84M | 1.1 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/msmarco.zip) | `444067daf65d982533ea17ebd59501e4` |
159
+ | TREC-COVID | [Homepage](https://ir.nist.gov/covidSubmit/index.html) | `trec-covid` | `test` | 50 | 171K | 493.5 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/trec-covid.zip) | `ce62140cb23feb9becf6270d0d1fe6d1` |
160
+ | NFCorpus | [Homepage](https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/) | `nfcorpus` | `train` `dev` `test` | 323 | 3.6K | 38.2 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/nfcorpus.zip) | `a89dba18a62ef92f7d323ec890a0d38d` |
161
+ | BioASQ | [Homepage](http://bioasq.org) | `bioasq` | `train` `test` | 500 | 14.91M | 8.05 | No | [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#2-bioasq) |
162
+ | NQ | [Homepage](https://ai.google.com/research/NaturalQuestions) | `nq` | `train` `test` | 3,452 | 2.68M | 1.2 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/nq.zip) | `d4d3d2e48787a744b6f6e691ff534307` |
163
+ | HotpotQA | [Homepage](https://hotpotqa.github.io) | `hotpotqa` | `train` `dev` `test` | 7,405 | 5.23M | 2.0 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/hotpotqa.zip) | `f412724f78b0d91183a0e86805e16114` |
164
+ | FiQA-2018 | [Homepage](https://sites.google.com/view/fiqa/) | `fiqa` | `train` `dev` `test` | 648 | 57K | 2.6 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/fiqa.zip) | `17918ed23cd04fb15047f73e6c3bd9d9` |
165
+ | Signal-1M(RT) | [Homepage](https://research.signal-ai.com/datasets/signal1m-tweetir.html) | `signal1m` | `test` | 97 | 2.86M | 19.6 | No | [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#4-signal-1m) |
166
+ | TREC-NEWS | [Homepage](https://trec.nist.gov/data/news2019.html) | `trec-news` | `test` | 57 | 595K | 19.6 | No | [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#1-trec-news) |
167
+ | ArguAna | [Homepage](http://argumentation.bplaced.net/arguana/data) | `arguana` | `test` | 1,406 | 8.67K | 1.0 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/arguana.zip) | `8ad3e3c2a5867cdced806d6503f29b99` |
168
+ | Touche-2020 | [Homepage](https://webis.de/events/touche-20/shared-task-1.html) | `webis-touche2020` | `test` | 49 | 382K | 19.0 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/webis-touche2020.zip) | `46f650ba5a527fc69e0a6521c5a23563` |
169
+ | CQADupstack | [Homepage](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/) | `cqadupstack` | `test` | 13,145 | 457K | 1.4 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/cqadupstack.zip) | `4e41456d7df8ee7760a7f866133bda78` |
170
+ | Quora | [Homepage](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs) | `quora` | `dev` `test` | 10,000 | 523K | 1.6 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/quora.zip) | `18fb154900ba42a600f84b839c173167` |
171
+ | DBPedia | [Homepage](https://github.com/iai-group/DBpedia-Entity/) | `dbpedia-entity` | `dev` `test` | 400 | 4.63M | 38.2 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/dbpedia-entity.zip) | `c2a39eb420a3164af735795df012ac2c` |
172
+ | SCIDOCS | [Homepage](https://allenai.org/data/scidocs) | `scidocs` | `test` | 1,000 | 25K | 4.9 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/scidocs.zip) | `38121350fc3a4d2f48850f6aff52e4a9` |
173
+ | FEVER | [Homepage](http://fever.ai) | `fever` | `train` `dev` `test` | 6,666 | 5.42M | 1.2 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/fever.zip) | `5a818580227bfb4b35bb6fa46d9b6c03` |
174
+ | Climate-FEVER | [Homepage](http://climatefever.ai) | `climate-fever` | `test` | 1,535 | 5.42M | 3.0 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/climate-fever.zip) | `8b66f0a9126c521bae2bde127b4dc99d` |
175
+ | SciFact | [Homepage](https://github.com/allenai/scifact) | `scifact` | `train` `test` | 300 | 5K | 1.1 | [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/scifact.zip) | `5f7d1de60b170fc8027bb7898e2efca1` |
176
+ | Robust04 | [Homepage](https://trec.nist.gov/data/robust/04.guidelines.html) | `robust04` | `test` | 249 | 528K | 69.9 | No | [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#3-robust04) |
177
+
178
+ ## Citation Information
179
+
180
+ ```bibtex
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
181
  @inproceedings{
182
  thakur2021beir,
183
  title={{BEIR}: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models},
 
187
  url={https://openreview.net/forum?id=wCu6T5xFjeJ}
188
  }
189
  ```
 
 
 
 
corpus/corpus-00000-of-00001.parquet CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6d63810663c22a21d74f1689da586ecdc1aec941d4d99494b2a5f319f3078471
3
- size 3193804
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f2a1c0b570a5efdf23cfa36f5e573d062cc113c6e7251e22c69b323a33ea895e
3
+ size 3157570
queries/queries-00000-of-00001.parquet CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:947d272a11835ab4690bb085928f951f26144bd4ecbc811dc48886297aa10b42
3
- size 83904
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:edd2b878b8130fb3b5e3c4b9428ddc1e67fbd6eedf8ae099fca3b87838ba6b29
3
+ size 80929