---
annotations_creators:
- machine-translated
language_creators:
- machine-translated
language:
- zh
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- squad_v2
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extractive-qa
pretty_name: Chinese SQuAD 2.0
---

# Dataset Card for Chinese SQuAD 2.0

## Dataset Description

### Dataset Summary

This is a Chinese translation of the SQuAD 2.0 dataset, translated from the original English version. Like SQuAD 2.0, it contains both answerable and unanswerable questions. The dataset is designed for Chinese reading comprehension and question answering tasks.

Source: [ChineseSquad](https://github.com/junzeng-pluto/ChineseSquad)

### Dataset Structure

The dataset is stored in Parquet format and contains the following fields:

```python
{
    'id': string,
    'title': string,
    'context': string,
    'question': string,
    'answers': {
        'text': List[string],
        'answer_start': List[int]
    }
}
```

### Data Splits

| Split      | Total Examples | Answerable | Unanswerable |
|------------|---------------|------------|--------------|
| train      | 90,027        | 46,529     | 43,498       |
| validation | 9,936         | 3,991      | 5,945        |

### Usage

```python
from datasets import load_dataset

# Load from Hugging Face Hub
dataset = load_dataset("real-jiakai/chinese-squadv2")

# Example usage
example = dataset['train'][0]
print(f"Question: {example['question']}")
print(f"Context: {example['context']}")
print(f"Answer: {example['answers']['text']}")
```

Example output:

```python
Question: 碧昂丝在成长过程中，在哪些领域竞争？
Context: 碧昂丝·吉赛尔·诺尔斯·卡特（生于1981年9月4日）是美国歌手、作曲家、唱片制作人和女演员。她在得克萨斯州休斯顿出生长大，小时候参加过各种歌舞比赛，上世纪90年代末以R&B女团“命运之子”的主唱而声名鹊起。由她父亲马修·诺尔斯（Mathew Knowles）管理的这个集团，一直以来都是世界上最畅销的女孩集团之一。暂停期间，碧昂丝发行了首张专辑《恋爱中的危险》（2003），确立了她作为全球独唱艺术家的地位，获得了五项格莱美奖，并在广告牌上热播100首单曲《疯狂恋爱》和《小男孩》。
Answer: ['歌舞']
```

### Citation

If you use this dataset, please cite both the original SQuAD 2.0 paper and the Chinese translation:

```bibtex
@inproceedings{rajpurkar-etal-2018-know,
    title = "Know What You Don{'}t Know: Unanswerable Questions for {SQ}u{AD}",
    author = "Rajpurkar, Pranav  and
      Jia, Robin  and
      Liang, Percy",
    editor = "Gurevych, Iryna  and
      Miyao, Yusuke",
    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P18-2124",
    doi = "10.18653/v1/P18-2124",
    pages = "784--789",
    eprint={1806.03822},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

@inproceedings{rajpurkar-etal-2016-squad,
    title = "{SQ}u{AD}: 100,000+ Questions for Machine Comprehension of Text",
    author = "Rajpurkar, Pranav  and
      Zhang, Jian  and
      Lopyrev, Konstantin  and
      Liang, Percy",
    editor = "Su, Jian  and
      Duh, Kevin  and
      Carreras, Xavier",
    booktitle = "Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2016",
    address = "Austin, Texas",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/D16-1264",
    doi = "10.18653/v1/D16-1264",
    pages = "2383--2392",
    eprint={1606.05250},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
}

@misc{ChineseSquad,
    title = "ChineseSquad",
    author = "junzeng-pluto",
    url = "https://github.com/junzeng-pluto/ChineseSquad",
}
```

### License

This dataset is licensed under CC BY-SA 4.0, following the original SQuAD 2.0 license.

### Limitations and Bias

- Current version contains ~100k examples, which is less than the original SQuAD 2.0
- As a machine-translated dataset, some nuances from the original English text might be lost or altered
- The answer spans are machine-aligned after translation, which might introduce some noise
- The dataset inherits any biases present in the original SQuAD 2.0 dataset
- Translation quality may vary across different examples