task_categories:question-answering task_ids:extractive-qa annotations_creators:expert-generated language_creators:expert-generated multilinguality:multilingual size_categories:unknown source_datasets:extended|squad language:ar language:de language:el language:en language:es language:hi language:ro language:ru language:th language:tr language:vi language:zh license:cc-by-sa-4.0 arxiv:1910.11856 region:us
XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering
performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set
of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translations into ten languages: Spanish, German,
Greek, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, Hindi and Romanian. Consequently, the dataset is entirely parallel
across 12 languages.
@article{Artetxe:etal:2019,
      author    = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
      title     = {On the cross-lingual transferability of monolingual representations},
      journal   = {CoRR},
      volume    = {abs/1910.11856},
      year      = {2019},
      archivePrefix = {arXiv},
      eprint    = {1910.11856}
}
---
pretty_name: XQuAD
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ar
- de
- el
- en
- es
- hi
- ro
- ru
- th
- tr
- vi
- zh
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- unknown
source_datasets:
- extended|squad
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: xquad
dataset_info:
- config_name: xquad.ar
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 1722799
    num_examples: 1190
  download_size: 13962158
  dataset_size: 1722799
- config_name: xquad.de
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 1283301
    num_examples: 1190
  download_size: 13962158
  dataset_size: 1283301
- config_name: xquad.zh
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 984241
    num_examples: 1190
  download_size: 13962158
  dataset_size: 984241
- config_name: xquad.vi
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 1477239
    num_examples: 1190
  download_size: 13962158
  dataset_size: 1477239
- config_name: xquad.en
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 1116123
    num_examples: 1190
  download_size: 13962158
  dataset_size: 1116123
- config_name: xquad.es
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 1273499
    num_examples: 1190
  download_size: 13962158
  dataset_size: 1273499
- config_name: xquad.hi
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 2682975
    num_examples: 1190
  download_size: 13962158
  dataset_size: 2682975
- config_name: xquad.el
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 2206690
    num_examples: 1190
  download_size: 13962158
  dataset_size: 2206690
- config_name: xquad.th
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 2854959
    num_examples: 1190
  download_size: 13962158
  dataset_size: 2854959
- config_name: xquad.tr
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 1210763
    num_examples: 1190
  download_size: 13962158
  dataset_size: 1210763
- config_name: xquad.ru
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 2136990
    num_examples: 1190
  download_size: 13962158
  dataset_size: 2136990
- config_name: xquad.ro
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: validation
    num_bytes: 1299450
    num_examples: 1190
  download_size: 13962158
  dataset_size: 1299450
---

# Dataset Card for "xquad"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [https://github.com/deepmind/xquad](https://github.com/deepmind/xquad)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 146.31 MB
- **Size of the generated dataset:** 18.97 MB
- **Total amount of disk used:** 165.28 MB

### Dataset Summary

XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering
performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set
of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translations into ten languages: Spanish, German,
Greek, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, and Hindi. Consequently, the dataset is entirely parallel
across 11 languages.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### xquad.ar

- **Size of downloaded dataset files:** 13.30 MB
- **Size of the generated dataset:** 1.72 MB
- **Total amount of disk used:** 15.03 MB

An example of 'validation' looks as follows.
```
This example was too long and was cropped:

{
    "answers": {
        "answer_start": [527],
        "text": ["136"]
    },
    "context": "\"Die Verteidigung der Panthers gab nur 308 Punkte ab und belegte den sechsten Platz in der Liga, während sie die NFL mit 24 Inte...",
    "id": "56beb4343aeaaa14008c925c",
    "question": "Wie viele Sacks erzielte Jared Allen in seiner Karriere?"
}
```

#### xquad.de

- **Size of downloaded dataset files:** 13.30 MB
- **Size of the generated dataset:** 1.29 MB
- **Total amount of disk used:** 14.59 MB

An example of 'validation' looks as follows.
```
This example was too long and was cropped:

{
    "answers": {
        "answer_start": [527],
        "text": ["136"]
    },
    "context": "\"Die Verteidigung der Panthers gab nur 308 Punkte ab und belegte den sechsten Platz in der Liga, während sie die NFL mit 24 Inte...",
    "id": "56beb4343aeaaa14008c925c",
    "question": "Wie viele Sacks erzielte Jared Allen in seiner Karriere?"
}
```

#### xquad.el

- **Size of downloaded dataset files:** 13.30 MB
- **Size of the generated dataset:** 2.21 MB
- **Total amount of disk used:** 15.51 MB

An example of 'validation' looks as follows.
```
This example was too long and was cropped:

{
    "answers": {
        "answer_start": [527],
        "text": ["136"]
    },
    "context": "\"Die Verteidigung der Panthers gab nur 308 Punkte ab und belegte den sechsten Platz in der Liga, während sie die NFL mit 24 Inte...",
    "id": "56beb4343aeaaa14008c925c",
    "question": "Wie viele Sacks erzielte Jared Allen in seiner Karriere?"
}
```

#### xquad.en

- **Size of downloaded dataset files:** 13.30 MB
- **Size of the generated dataset:** 1.12 MB
- **Total amount of disk used:** 14.42 MB

An example of 'validation' looks as follows.
```
This example was too long and was cropped:

{
    "answers": {
        "answer_start": [527],
        "text": ["136"]
    },
    "context": "\"Die Verteidigung der Panthers gab nur 308 Punkte ab und belegte den sechsten Platz in der Liga, während sie die NFL mit 24 Inte...",
    "id": "56beb4343aeaaa14008c925c",
    "question": "Wie viele Sacks erzielte Jared Allen in seiner Karriere?"
}
```

#### xquad.es

- **Size of downloaded dataset files:** 13.30 MB
- **Size of the generated dataset:** 1.28 MB
- **Total amount of disk used:** 14.58 MB

An example of 'validation' looks as follows.
```
This example was too long and was cropped:

{
    "answers": {
        "answer_start": [527],
        "text": ["136"]
    },
    "context": "\"Die Verteidigung der Panthers gab nur 308 Punkte ab und belegte den sechsten Platz in der Liga, während sie die NFL mit 24 Inte...",
    "id": "56beb4343aeaaa14008c925c",
    "question": "Wie viele Sacks erzielte Jared Allen in seiner Karriere?"
}
```

### Data Fields

The data fields are the same among all splits.

#### xquad.ar
- `id`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `answer_start`: a `int32` feature.

#### xquad.de
- `id`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `answer_start`: a `int32` feature.

#### xquad.el
- `id`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `answer_start`: a `int32` feature.

#### xquad.en
- `id`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `answer_start`: a `int32` feature.

#### xquad.es
- `id`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `answer_start`: a `int32` feature.

### Data Splits

| name     | validation |
| -------- | ---------: |
| xquad.ar |       1190 |
| xquad.de |       1190 |
| xquad.el |       1190 |
| xquad.en |       1190 |
| xquad.es |       1190 |

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@article{Artetxe:etal:2019,
      author    = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
      title     = {On the cross-lingual transferability of monolingual representations},
      journal   = {CoRR},
      volume    = {abs/1910.11856},
      year      = {2019},
      archivePrefix = {arXiv},
      eprint    = {1910.11856}
}

```


### Contributions

Thanks to [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset.