mlqa
Stay organized with collections
Save and categorize content based on your preferences.
MLQA (Multilingual Question Answering Dataset) is a benchmark dataset for
evaluating multilingual question answering performance. The dataset consists of
7 languages: Arabic, German, Spanish, English, Hindi, Vietnamese, Chinese.
FeaturesDict({
'answers': Sequence({
'answer_start': int32,
'text': Text(shape=(), dtype=string),
}),
'context': Text(shape=(), dtype=string),
'id': string,
'question': Text(shape=(), dtype=string),
'title': Text(shape=(), dtype=string),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
answers |
Sequence |
|
|
|
answers/answer_start |
Tensor |
|
int32 |
|
answers/text |
Text |
|
string |
|
context |
Text |
|
string |
|
id |
Tensor |
|
string |
|
question |
Text |
|
string |
|
title |
Text |
|
string |
|
@article{lewis2019mlqa,
title={MLQA: Evaluating Cross-lingual Extractive Question Answering},
author={Lewis, Patrick and Ouguz, Barlas and Rinott, Ruty and Riedel, Sebastian and Schwenk, Holger},
journal={arXiv preprint arXiv:1910.07475},
year={2019}
}
mlqa/ar (default config)
Split |
Examples |
'test' |
5,335 |
'validation' |
517 |
mlqa/de
Split |
Examples |
'test' |
4,517 |
'validation' |
512 |
mlqa/en
Split |
Examples |
'test' |
11,590 |
'validation' |
1,148 |
mlqa/es
Split |
Examples |
'test' |
5,253 |
'validation' |
500 |
mlqa/hi
Split |
Examples |
'test' |
4,918 |
'validation' |
507 |
mlqa/vi
Split |
Examples |
'test' |
5,495 |
'validation' |
511 |
mlqa/zh
Split |
Examples |
'test' |
5,137 |
'validation' |
504 |
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2022-12-14 UTC.
[null,null,["Last updated 2022-12-14 UTC."],[],[],null,["# mlqa\n\n\u003cbr /\u003e\n\n- **Description**:\n\nMLQA (Multilingual Question Answering Dataset) is a benchmark dataset for\nevaluating multilingual question answering performance. The dataset consists of\n7 languages: Arabic, German, Spanish, English, Hindi, Vietnamese, Chinese.\n\n- **Additional Documentation** :\n [Explore on Papers With Code\n north_east](https://paperswithcode.com/dataset/mlqa)\n\n- **Homepage** :\n \u003chttps://github.com/facebookresearch/MLQA\u003e\n\n- **Source code** :\n [`tfds.datasets.mlqa.Builder`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/datasets/mlqa/mlqa_dataset_builder.py)\n\n- **Versions**:\n\n - **`1.0.0`** (default): No release notes.\n- **Download size** : `72.21 MiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n Yes\n\n- **Feature structure**:\n\n FeaturesDict({\n 'answers': Sequence({\n 'answer_start': int32,\n 'text': Text(shape=(), dtype=string),\n }),\n 'context': Text(shape=(), dtype=string),\n 'id': string,\n 'question': Text(shape=(), dtype=string),\n 'title': Text(shape=(), dtype=string),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|----------------------|--------------|-------|--------|-------------|\n| | FeaturesDict | | | |\n| answers | Sequence | | | |\n| answers/answer_start | Tensor | | int32 | |\n| answers/text | Text | | string | |\n| context | Text | | string | |\n| id | Tensor | | string | |\n| question | Text | | string | |\n| title | Text | | string | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `None`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Citation**:\n\n @article{lewis2019mlqa,\n title={MLQA: Evaluating Cross-lingual Extractive Question Answering},\n author={Lewis, Patrick and Ouguz, Barlas and Rinott, Ruty and Riedel, Sebastian and Schwenk, Holger},\n journal={arXiv preprint arXiv:1910.07475},\n year={2019}\n }\n\nmlqa/ar (default config)\n------------------------\n\n- **Config description**: MLQA 'ar' dev and test splits.\n\n- **Dataset size** : `9.28 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'test'` | 5,335 |\n| `'validation'` | 517 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nmlqa/de\n-------\n\n- **Config description**: MLQA 'de' dev and test splits.\n\n- **Dataset size** : `5.06 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'test'` | 4,517 |\n| `'validation'` | 512 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nmlqa/en\n-------\n\n- **Config description**: MLQA 'en' dev and test splits.\n\n- **Dataset size** : `15.72 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'test'` | 11,590 |\n| `'validation'` | 1,148 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nmlqa/es\n-------\n\n- **Config description**: MLQA 'es' dev and test splits.\n\n- **Dataset size** : `5.09 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'test'` | 5,253 |\n| `'validation'` | 500 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nmlqa/hi\n-------\n\n- **Config description**: MLQA 'hi' dev and test splits.\n\n- **Dataset size** : `12.83 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'test'` | 4,918 |\n| `'validation'` | 507 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nmlqa/vi\n-------\n\n- **Config description**: MLQA 'vi' dev and test splits.\n\n- **Dataset size** : `8.77 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'test'` | 5,495 |\n| `'validation'` | 511 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nmlqa/zh\n-------\n\n- **Config description**: MLQA 'zh' dev and test splits.\n\n- **Dataset size** : `5.13 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'test'` | 5,137 |\n| `'validation'` | 504 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples..."]]