irds/kilt_codec_politics

---
pretty_name: '`kilt/codec/politics`'
viewer: false
source_datasets: []
task_categories:
- text-retrieval
---

# Dataset Card for `kilt/codec/politics`

The `kilt/codec/politics` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/kilt#kilt/codec/politics).

# Data

This dataset provides:
- `queries` (i.e., topics); count=14
- `qrels`: (relevance assessments); count=2,192

## Usage

```python
from datasets import load_dataset

queries = load_dataset('irds/kilt_codec_politics', 'queries')
for record in queries:
record # {'query_id': ..., 'query': ..., 'domain': ..., 'guidelines': ...}

qrels = load_dataset('irds/kilt_codec_politics', '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{mackie2022codec,
title={CODEC: Complex Document and Entity Collection},
author={Mackie, Iain and Owoicho, Paul and Gemmell, Carlos and Fischer, Sophie and MacAvaney, Sean and Dalton, Jeffery},
booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
year={2022}
}
```

原始信息汇总

数据集概述

数据集名称

kilt/codec/politics

数据来源

由 ir-datasets 包提供。

数据内容

• queries（即主题）：数量为14个。
• qrels（相关性评估）：数量为2,192个。

数据使用示例

python from datasets import load_dataset

queries = load_dataset(irds/kilt_codec_politics, queries) for record in queries: record # {query_id: ..., query: ..., domain: ..., guidelines: ...}

qrels = load_dataset(irds/kilt_codec_politics, qrels) for record in qrels: record # {query_id: ..., doc_id: ..., relevance: ...}

引用信息

@inproceedings{mackie2022codec, title={CODEC: Complex Document and Entity Collection}, author={Mackie, Iain and Owoicho, Paul and Gemmell, Carlos and Fischer, Sophie and MacAvaney, Sean and Dalton, Jeffery}, booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval}, year={2022} }