README.md

metadata

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: 4993889
        num_examples: 8674
    download_size: 4993889
    dataset_size: 4993889
  - config_name: queries
    features:
      - name: _id
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: queries
        num_bytes: 949777
        num_examples: 1406
    download_size: 949777
    dataset_size: 949777

Dataset Card for BEIR Benchmark

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.

This arguana subset is the Argument Retrieval task within BEIR.

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:

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},
}

Data Splits

Subset	Split	Rows
corpus	corpus	8,674
queries	queries	1,406

NFCorpus Data Splits

• train, dev, test

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	msmarco	train dev test	6,980	8.84M	1.1	Link	444067daf65d982533ea17ebd59501e4
TREC-COVID	Homepage	trec-covid	test	50	171K	493.5	Link	ce62140cb23feb9becf6270d0d1fe6d1
NFCorpus	Homepage	nfcorpus	train dev test	323	3.6K	38.2	Link	a89dba18a62ef92f7d323ec890a0d38d
BioASQ	Homepage	bioasq	train test	500	14.91M	8.05	No	How to Reproduce?
NQ	Homepage	nq	train test	3,452	2.68M	1.2	Link	d4d3d2e48787a744b6f6e691ff534307
HotpotQA	Homepage	hotpotqa	train dev test	7,405	5.23M	2.0	Link	f412724f78b0d91183a0e86805e16114
FiQA-2018	Homepage	fiqa	train dev test	648	57K	2.6	Link	17918ed23cd04fb15047f73e6c3bd9d9
Signal-1M(RT)	Homepage	signal1m	test	97	2.86M	19.6	No	How to Reproduce?
TREC-NEWS	Homepage	trec-news	test	57	595K	19.6	No	How to Reproduce?
ArguAna	Homepage	arguana	test	1,406	8.67K	1.0	Link	8ad3e3c2a5867cdced806d6503f29b99
Touche-2020	Homepage	webis-touche2020	test	49	382K	19.0	Link	46f650ba5a527fc69e0a6521c5a23563
CQADupstack	Homepage	cqadupstack	test	13,145	457K	1.4	Link	4e41456d7df8ee7760a7f866133bda78
Quora	Homepage	quora	dev test	10,000	523K	1.6	Link	18fb154900ba42a600f84b839c173167
DBPedia	Homepage	dbpedia-entity	dev test	400	4.63M	38.2	Link	c2a39eb420a3164af735795df012ac2c
SCIDOCS	Homepage	scidocs	test	1,000	25K	4.9	Link	38121350fc3a4d2f48850f6aff52e4a9
FEVER	Homepage	fever	train dev test	6,666	5.42M	1.2	Link	5a818580227bfb4b35bb6fa46d9b6c03
Climate-FEVER	Homepage	climate-fever	test	1,535	5.42M	3.0	Link	8b66f0a9126c521bae2bde127b4dc99d
SciFact	Homepage	scifact	train test	300	5K	1.1	Link	5f7d1de60b170fc8027bb7898e2efca1
Robust04	Homepage	robust04	test	249	528K	69.9	No	How to Reproduce?

Citation Information

@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}
}