Datasets:
Tasks:
Text Retrieval
ArXiv:
metadata
pretty_name: '`beir/fiqa/train`'
viewer: false
source_datasets:
- irds/beir_fiqa
task_categories:
- text-retrieval
Dataset Card for beir/fiqa/train
The beir/fiqa/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=5,500qrels
: (relevance assessments); count=14,166For
docs
, useirds/beir_fiqa
Usage
from datasets import load_dataset
queries = load_dataset('irds/beir_fiqa_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/beir_fiqa_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
@article{Maia2018Fiqa,
title={WWW'18 Open Challenge: Financial Opinion Mining and Question Answering},
author={Macedo Maia and S. Handschuh and A. Freitas and Brian Davis and R. McDermott and M. Zarrouk and A. Balahur},
journal={Companion Proceedings of the The Web Conference 2018},
year={2018}
}
@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",
}