irds/beir_nq

Dataset Card for beir/nq

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

Data

This dataset provides:

• docs (documents, i.e., the corpus); count=2,681,468
• queries (i.e., topics); count=3,452
• qrels: (relevance assessments); count=4,201

Usage

from datasets import load_dataset

docs = load_dataset('irds/beir_nq', 'docs')
for record in docs:
    record # {'doc_id': ..., 'text': ..., 'title': ...}

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

qrels = load_dataset('irds/beir_nq', '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

@article{Kwiatkowski2019Nq,
  title = {Natural Questions: a Benchmark for Question Answering Research},
  author = {Tom Kwiatkowski and Jennimaria Palomaki and Olivia Redfield and Michael Collins and Ankur Parikh and Chris Alberti and Danielle Epstein and Illia Polosukhin and Matthew Kelcey and Jacob Devlin and Kenton Lee and Kristina N. Toutanova and Llion Jones and Ming-Wei Chang and Andrew Dai and Jakob Uszkoreit and Quoc Le and Slav Petrov},
  year = {2019},
  journal = {TACL}
}
@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",
}