BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Paper
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2104.08663
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Published
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3
beir/arguana
The beir/arguana dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
This dataset provides:
docs (documents, i.e., the corpus); count=8,674queries (i.e., topics); count=1,406qrels: (relevance assessments); count=1,406from datasets import load_dataset
docs = load_dataset('irds/beir_arguana', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ..., 'title': ...}
queries = load_dataset('irds/beir_arguana', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/beir_arguana', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
Note that calling load_dataset will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
@inproceedings{Wachsmuth2018Arguana,
author = "Wachsmuth, Henning and Syed, Shahbaz and Stein, Benno",
title = "Retrieval of the Best Counterargument without Prior Topic Knowledge",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
year = "2018",
publisher = "Association for Computational Linguistics",
location = "Melbourne, Australia",
pages = "241--251",
url = "http://aclweb.org/anthology/P18-1023"
}
@article{Thakur2021Beir,
title = "BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models",
author = "Thakur, Nandan and Reimers, Nils and Rücklé, Andreas and Srivastava, Abhishek and Gurevych, Iryna",
journal= "arXiv preprint arXiv:2104.08663",
month = "4",
year = "2021",
url = "https://arxiv.org/abs/2104.08663",
}