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irds/antique_test_non-offensive

Dataset Card for antique/test/non-offensive The antique/test/non-offensive 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=176 qrels: (relevance assessments); count=5,752 For docs, use irds/antique Usage from datasets import load_dataset queries = load_dataset('irds/antique_test_non-offensive', 'queries') for record in… See the full description on the dataset page: https://huggingface.co/datasets/irds/antique_test_non-offensive.

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Dataset Card

Dataset Card for `antique/test/non-offensive`

The antique/test/non-offensive 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=176
—qrels: (relevance assessments); count=5,752

—For docs, use `irds/antique`

Usage

python

from datasets import load_dataset

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

qrels = load_dataset('irds/antique_test_non-offensive', '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}
}