irds/antique_train_split200-train
Dataset Card for antique/train/split200-train The antique/train/split200-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=2,226 qrels: (relevance assessments); count=25,229 For docs, use irds/antique Usage from datasets import load_dataset queries = load_dataset('irds/antique_train_split200-train', 'queries') for record… See the full description on the dataset page: https://huggingface.co/datasets/irds/antique_train_split200-train.
Dataset Card for antique/train/split200-train
The antique/train/split200-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=2,226qrels: (relevance assessments); count=25,229
- For
docs, use `irds/antique`
Usage
from datasets import load_dataset
queries = load_dataset('irds/antique_train_split200-train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/antique_train_split200-train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
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{Hashemi2020Antique,
title={ANTIQUE: A Non-Factoid Question Answering Benchmark},
author={Helia Hashemi and Mohammad Aliannejadi and Hamed Zamani and Bruce Croft},
booktitle={ECIR},
year={2020}
}