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pretty_name: '`nfcorpus/dev`'
viewer: false
source_datasets: ['irds/nfcorpus']
task_categories:
- text-retrieval
---
# Dataset Card for `nfcorpus/dev`
The `nfcorpus/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/nfcorpus#nfcorpus/dev).
# Data
This dataset provides:
- `queries` (i.e., topics); count=325
- `qrels`: (relevance assessments); count=14,589
- For `docs`, use [`irds/nfcorpus`](https://huggingface.co/datasets/irds/nfcorpus)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/nfcorpus_dev', 'queries')
for record in queries:
record # {'query_id': ..., 'title': ..., 'all': ...}
qrels = load_dataset('irds/nfcorpus_dev', '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{Boteva2016Nfcorpus,
title="A Full-Text Learning to Rank Dataset for Medical Information Retrieval",
author = "Vera Boteva and Demian Gholipour and Artem Sokolov and Stefan Riezler",
booktitle = "Proceedings of the European Conference on Information Retrieval ({ECIR})",
location = "Padova, Italy",
publisher = "Springer",
year = 2016
}
```
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