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---
pretty_name: '`antique/train`'
viewer: false
source_datasets: ['irds/antique']
task_categories:
- text-retrieval
---
# Dataset Card for `antique/train`
The `antique/train` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/antique#antique/train).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,426
- `qrels`: (relevance assessments); count=27,422
- For `docs`, use [`irds/antique`](https://huggingface.co/datasets/irds/antique)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/antique_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/antique_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{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}
}
```
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