irds/beir_msmarco_train

Dataset Card for beir/msmarco/train

The beir/msmarco/train 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=502,939

• qrels: (relevance assessments); count=532,751

• For docs, use irds/beir_msmarco

Usage

from datasets import load_dataset

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

qrels = load_dataset('irds/beir_msmarco_train', '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{Bajaj2016Msmarco,
  title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
  author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
  booktitle={InCoCo@NIPS},
  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",
}