References:
de
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:mlsum/de')
- Description:
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset.
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish.
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community.
We report cross-lingual comparative analyses based on state-of-the-art systems.
These highlight existing biases which motivate the use of a multi-lingual dataset.
- License: No known license
- Version: 1.0.0
- Splits:
| Split | Examples |
|---|---|
'test' |
10701 |
'train' |
220887 |
'validation' |
11394 |
- Features:
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"summary": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"topic": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
es
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:mlsum/es')
- Description:
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset.
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish.
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community.
We report cross-lingual comparative analyses based on state-of-the-art systems.
These highlight existing biases which motivate the use of a multi-lingual dataset.
- License: No known license
- Version: 1.0.0
- Splits:
| Split | Examples |
|---|---|
'test' |
13920 |
'train' |
266367 |
'validation' |
10358 |
- Features:
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"summary": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"topic": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
fr
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:mlsum/fr')
- Description:
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset.
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish.
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community.
We report cross-lingual comparative analyses based on state-of-the-art systems.
These highlight existing biases which motivate the use of a multi-lingual dataset.
- License: No known license
- Version: 1.0.0
- Splits:
| Split | Examples |
|---|---|
'test' |
15828 |
'train' |
392902 |
'validation' |
16059 |
- Features:
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"summary": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"topic": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ru
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:mlsum/ru')
- Description:
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset.
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish.
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community.
We report cross-lingual comparative analyses based on state-of-the-art systems.
These highlight existing biases which motivate the use of a multi-lingual dataset.
- License: No known license
- Version: 1.0.0
- Splits:
| Split | Examples |
|---|---|
'test' |
757 |
'train' |
25556 |
'validation' |
750 |
- Features:
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"summary": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"topic": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
tu
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:mlsum/tu')
- Description:
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset.
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish.
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community.
We report cross-lingual comparative analyses based on state-of-the-art systems.
These highlight existing biases which motivate the use of a multi-lingual dataset.
- License: No known license
- Version: 1.0.0
- Splits:
| Split | Examples |
|---|---|
'test' |
12775 |
'train' |
249277 |
'validation' |
11565 |
- Features:
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"summary": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"topic": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}