irds/mr-tydi_th

---
pretty_name: '`mr-tydi/th`'
viewer: false
source_datasets: []
task_categories:
- text-retrieval
---

# Dataset Card for `mr-tydi/th`

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

# Data

This dataset provides:
- `docs` (documents, i.e., the corpus); count=568,855
- `queries` (i.e., topics); count=5,322
- `qrels`: (relevance assessments); count=5,545

This dataset is used by: [`mr-tydi_th_dev`](https://huggingface.co/datasets/irds/mr-tydi_th_dev), [`mr-tydi_th_test`](https://huggingface.co/datasets/irds/mr-tydi_th_test), [`mr-tydi_th_train`](https://huggingface.co/datasets/irds/mr-tydi_th_train)

## Usage

```python
from datasets import load_dataset

docs = load_dataset('irds/mr-tydi_th', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}

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

qrels = load_dataset('irds/mr-tydi_th', '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

```
@article{Zhang2021MrTyDi,
title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval},
author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin},
year={2021},
journal={arXiv:2108.08787},
}
@article{Clark2020TyDiQa,
title={{TyDi QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages},
author={Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki},
year={2020},
journal={Transactions of the Association for Computational Linguistics}
}
```

原始信息汇总

数据集卡片 mr-tydi/th

数据集概述

mr-tydi/th 数据集由 ir-datasets 包提供。

数据内容

该数据集包含以下内容：

• docs：文档（即语料库），数量为 568,855。
• queries：查询（即主题），数量为 5,322。
• qrels：相关性评估，数量为 5,545。

使用方法

以下是加载和使用该数据集的示例代码： python from datasets import load_dataset

docs = load_dataset(irds/mr-tydi_th, docs) for record in docs: record # {doc_id: ..., text: ...}

queries = load_dataset(irds/mr-tydi_th, queries) for record in queries: record # {query_id: ..., text: ...}

qrels = load_dataset(irds/mr-tydi_th, qrels) for record in qrels: record # {query_id: ..., doc_id: ..., relevance: ..., iteration: ...}

引用信息

@article{Zhang2021MrTyDi, title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval}, author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin}, year={2021}, journal={arXiv:2108.08787}, } @article{Clark2020TyDiQa, title={{TyDi QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages}, author={Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}, year={2020}, journal={Transactions of the Association for Computational Linguistics} }