irds/mr-tydi_bn_train

---
pretty_name: '`mr-tydi/bn/train`'
viewer: false
source_datasets: ['irds/mr-tydi_bn']
task_categories:
- text-retrieval
---

# Dataset Card for `mr-tydi/bn/train`

The `mr-tydi/bn/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/mr-tydi#mr-tydi/bn/train).

# Data

This dataset provides:
- `queries` (i.e., topics); count=1,713
- `qrels`: (relevance assessments); count=1,719

- For `docs`, use [`irds/mr-tydi_bn`](https://huggingface.co/datasets/irds/mr-tydi_bn)

## Usage

```python
from datasets import load_dataset

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

qrels = load_dataset('irds/mr-tydi_bn_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

```
@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}
}
```

pretty_name: '`mr-tydi/bn/train`'
viewer: false
source_datasets: ['irds/mr-tydi_bn']
task_categories:
- 文本检索

# `mr-tydi/bn/train` 数据集卡片

本`mr-tydi/bn/train`数据集由[ir-datasets](https://ir-datasets.com/)工具包提供。如需了解该数据集的更多详情，请参阅[官方文档](https://ir-datasets.com/mr-tydi#mr-tydi/bn/train)。

# 数据集内容

本数据集包含以下内容：
- `queries`（即查询主题）：共计1,713条
- `qrels`（相关性标注结果）：共计1,719条

如需获取`docs`（文档数据），请使用 [`irds/mr-tydi_bn`](https://huggingface.co/datasets/irds/mr-tydi_bn)

# 使用方法

python
from datasets import load_dataset

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

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

请注意，调用`load_dataset`函数将自动下载该数据集（若数据集未公开，则会提供获取指引），并将数据转换为🤗数据集格式后存储副本。

# 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}
}

原始信息汇总

数据集卡片 mr-tydi/bn/train

数据集概述

mr-tydi/bn/train 数据集由 ir-datasets 包提供。

数据内容

该数据集包含以下内容：

• queries（即主题）；数量=1,713
• qrels（相关性评估）；数量=1,719

对于 docs，请使用 irds/mr-tydi_bn。

使用方法

以下是加载数据集的示例代码： python from datasets import load_dataset

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

qrels = load_dataset(irds/mr-tydi_bn_train, 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} }