Duplicate from BeIR/scifact

Co-authored-by: Nandan Thakur <nthakur@users.noreply.huggingface.co>

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README.md

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+---
+language:
+- en
+license:
+- cc-by-sa-4.0
+multilinguality:
+- monolingual
+paperswithcode_id: beir
+pretty_name: BEIR Benchmark
+task_categories:
+- zero-shot-classification
+- text-retrieval
+task_ids:
+- document-retrieval
+- entity-linking-retrieval
+- fact-checking-retrieval
+tags:
+- biomedical-information-retrieval
+- citation-prediction-retrieval
+- passage-retrieval
+- news-retrieval
+- argument-retrieval
+- zero-shot-information-retrieval
+- tweet-retrieval
+- question-answering-retrieval
+- duplication-question-retrieval
+- zero-shot-retrieval
+configs:
+- config_name: corpus
+  data_files:
+  - split: corpus
+    path: corpus/corpus-*
+- config_name: queries
+  data_files:
+  - split: queries
+    path: queries/queries-*
+dataset_info:
+- config_name: corpus
+  features:
+  - name: _id
+    dtype: string
+  - name: title
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: corpus
+    num_bytes: 4469916
+    num_examples: 5183
+  download_size: 4469916
+  dataset_size: 4469916
+- config_name: queries
+  features:
+  - name: _id
+    dtype: string
+  - name: title
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: queries
+    num_bytes: 64982
+    num_examples: 1109
+  download_size: 64982
+  dataset_size: 64982
+---
+
+# Dataset Card for BEIR Benchmark
+
+> **`scifact` is one of the datasets from the Fact Checking task within BEIR, measuring scientific article retrieval for a given scientific claim.**
+
+
+## Dataset Description
+
+- **Homepage:** https://beir.ai
+- **Repository:** https://beir.ai
+- **Paper:** https://openreview.net/forum?id=wCu6T5xFjeJ
+- **Leaderboard:** https://docs.google.com/spreadsheets/d/1L8aACyPaXrL8iEelJLGqlMqXKPX2oSP_R10pZoy77Ns
+- **Point of Contact:** nandan.thakur@uwaterloo.ca
+
+### Dataset Summary
+
+BEIR is a heterogeneous benchmark built from 18 diverse datasets representing 9 information retrieval tasks.
+
+- Fact-checking: [FEVER](http://fever.ai), [Climate-FEVER](http://climatefever.ai), [SciFact](https://github.com/allenai/scifact)
+- Question-Answering: [NQ](https://ai.google.com/research/NaturalQuestions), [HotpotQA](https://hotpotqa.github.io), [FiQA-2018](https://sites.google.com/view/fiqa/)
+- Bio-Medical IR: [TREC-COVID](https://ir.nist.gov/covidSubmit/index.html), [BioASQ](http://bioasq.org), [NFCorpus](https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/)
+- News Retrieval: [TREC-NEWS](https://trec.nist.gov/data/news2019.html), [Robust04](https://trec.nist.gov/data/robust/04.guidelines.html)
+- Argument Retrieval: [Touche-2020](https://webis.de/events/touche-20/shared-task-1.html), [ArguAna](tp://argumentation.bplaced.net/arguana/data)
+- Duplicate Question Retrieval: [Quora](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs), [CqaDupstack](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/)
+- Citation-Prediction: [SCIDOCS](https://allenai.org/data/scidocs)
+- Tweet Retrieval: [Signal-1M](https://research.signal-ai.com/datasets/signal1m-tweetir.html)
+- Entity Retrieval: [DBPedia](https://github.com/iai-group/DBpedia-Entity/)
+
+### Languages
+
+All tasks are in English (`en`).
+
+## Dataset Structure
+
+This dataset uses the standard BEIR retrieval layout and includes:
+
+- `corpus`: one row per document with `_id`, `title`, `text`
+- `queries`: one row per query with `_id`, `title`, `text`
+
+### Data Fields
+
+- `_id` (`string`): unique identifier
+- `title` (`string`): title (empty string when unavailable)
+- `text` (`string`): document/query text
+
+### Data Instances
+
+A high level example of any BEIR dataset:
+
+```python
+corpus = {
+    "doc1" : {
+        "title": "Albert Einstein",
+        "text": "Albert Einstein was a German-born theoretical physicist. who developed the theory of relativity, \
+                 one of the two pillars of modern physics (alongside quantum mechanics). His work is also known for \
+                 its influence on the philosophy of science. He is best known to the general public for his mass–energy \
+                 equivalence formula E = mc2, which has been dubbed 'the world's most famous equation'. He received the 1921 \
+                 Nobel Prize in Physics 'for his services to theoretical physics, and especially for his discovery of the law \
+                 of the photoelectric effect', a pivotal step in the development of quantum theory."
+        },
+    "doc2" : {
+        "title": "", # Keep title an empty string if not present
+        "text": "Wheat beer is a top-fermented beer which is brewed with a large proportion of wheat relative to the amount of \
+                 malted barley. The two main varieties are German Weißbier and Belgian witbier; other types include Lambic (made\
+                 with wild yeast), Berliner Weisse (a cloudy, sour beer), and Gose (a sour, salty beer)."
+    },
+}
+
+queries = {
+    "q1" : "Who developed the mass-energy equivalence formula?",
+    "q2" : "Which beer is brewed with a large proportion of wheat?"
+}
+
+qrels = {
+    "q1" : {"doc1": 1},
+    "q2" : {"doc2": 1},
+}
+```
+
+### Scifact Data Splits
+
+| Subset | Split | Rows |
+| --- | --- | ---: |
+| corpus | corpus | 5,183 |
+| queries | queries | 1,109 |
+
+### BEIR Direct Download
+
+You can also download BEIR datasets directly (without loading through Hugging Face datasets) using the links below.
+
+| Dataset | Website | BEIR-Name | Type | Queries | Corpus | Rel D/Q | Down-load | md5 |
+| --- | --- | --- | --- | ---: | ---: | ---: | --- | --- |
+| 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` |
+| 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` |
+| 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` |
+| 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) |
+| 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` |
+| 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` |
+| 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` |
+| 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) |
+| 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) |
+| 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` |
+| 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` |
+| 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` |
+| 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` |
+| 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` |
+| 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` |
+| 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` |
+| 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` |
+| 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` |
+| 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) |
+
+## Citation Information
+
+```bibtex
+@inproceedings{
+thakur2021beir,
+title={{BEIR}: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models},
+author={Nandan Thakur and Nils Reimers and Andreas R{\"u}ckl{\'e} and Abhishek Srivastava and Iryna Gurevych},
+booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},
+year={2021},
+url={https://openreview.net/forum?id=wCu6T5xFjeJ}
+}
+```

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