README.md

metadata

pretty_name: '`beir/nfcorpus/dev`'
viewer: false
source_datasets:
  - irds/beir_nfcorpus
task_categories:
  - text-retrieval

Dataset Card for beir/nfcorpus/dev

The beir/nfcorpus/dev dataset, provided by the ir-datasets package. For more information about the dataset, see the documentation.

Data

This dataset provides:

• queries (i.e., topics); count=324

• qrels: (relevance assessments); count=11,385

• For docs, use irds/beir_nfcorpus

Usage

from datasets import load_dataset

queries = load_dataset('irds/beir_nfcorpus_dev', 'queries')
for record in queries:
    record # {'query_id': ..., 'text': ...}

qrels = load_dataset('irds/beir_nfcorpus_dev', '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.

Citation Information

@inproceedings{Boteva2016Nfcorpus,
  title="A Full-Text Learning to Rank Dataset for Medical Information Retrieval",
  author = "Vera Boteva and Demian Gholipour and Artem Sokolov and Stefan Riezler",
  booktitle = "Proceedings of the European Conference on Information Retrieval ({ECIR})",
  location = "Padova, Italy",
  publisher = "Springer",
  year = 2016
}
@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",
}