参考：
mlsum_de
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/mlsum_de')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_covid' |
5058 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test' |
10695 |
'train' |
220748 |
'validation' |
11392 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"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"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
mlsum_es
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/mlsum_es')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_covid' |
1938 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test' |
13366 |
'train' |
259888 |
'validation' |
9977 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"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"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_es_en_v0
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_es_en_v0')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
19797 |
'train' |
79515 |
'validation' |
8835 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_ru_en_v0
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_ru_en_v0')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
9094 |
'train' |
36898 |
'validation' |
4100 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_tr_en_v0
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_tr_en_v0')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
808 |
'train' |
3193 |
'validation' |
355 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_vi_en_v0
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_vi_en_v0')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
2167 |
'train' |
9206 |
'validation' |
1023 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_arabic_ar
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_arabic_ar')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
5841 |
'train' |
20441 |
'validation' |
2919 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"ar",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"ar",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_chinese_zh
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_chinese_zh')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
3775 |
'train' |
13211 |
'validation' |
1886 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"zh",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"zh",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_czech_cs
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_czech_cs')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
1438 |
'train' |
5033 |
'validation' |
718 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"cs",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"cs",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_dutch_nl
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_dutch_nl')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
6248 |
'train' |
21866 |
'validation' |
3123 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"nl",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"nl",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_english_en
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_english_en')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
28614 |
'train' |
99020 |
'validation' |
13823 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"en",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"en",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_french_fr
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_french_fr')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
12731 |
'train' |
44556 |
'validation' |
6364 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"fr",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"fr",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_german_de
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_german_de')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
11669 |
'train' |
40839 |
'validation' |
5833 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"de",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"de",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_hindi_hi
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_hindi_hi')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
1984 |
'train' |
6942 |
'validation' |
991 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"hi",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"hi",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_indonesian_id
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_indonesian_id')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
9497 |
'train' |
33237 |
'validation' |
4747 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"id",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"id",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_italian_it
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_italian_it')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
10189 |
'train' |
35661 |
'validation' |
5093 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"it",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"it",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_japanese_ja
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_japanese_ja')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
2530 |
'train' |
8853 |
'validation' |
1264 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"ja",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"ja",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_korean_ko
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_korean_ko')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
2436 |
'train' |
8524 |
'validation' |
1216 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"ko",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"ko",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_portuguese_pt
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_portuguese_pt')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
16331 |
'train' |
57159 |
'validation' |
8165 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"pt",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"pt",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_russian_ru
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_russian_ru')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
10580 |
'train' |
37028 |
'validation' |
5288 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"ru",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"ru",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_spanish_es
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_spanish_es')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
22632 |
'train' |
79212 |
'validation' |
11316 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"es",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"es",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_thai_th
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_thai_th')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
2950 |
'train' |
10325 |
'validation' |
1475 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"th",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"th",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_turkish_tr
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_turkish_tr')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
900 |
'train' |
3148 |
'validation' |
449 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"tr",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"tr",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_vietnamese_vi
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_lingua_vietnamese_vi')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
3917 |
'train' |
13707 |
'validation' |
1957 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"vi",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"vi",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
xsum
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/xsum')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_backtranslation' |
500 |
'challenge_test_bfp_02' |
500 |
'challenge_test_bfp_05' |
500 |
'challenge_test_covid' |
401 |
'challenge_test_nopunc' |
500 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test' |
1166 |
'train' |
23206 |
'validation' |
1117 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"xsum_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"document": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
common_gen
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/common_gen')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_scramble' |
500 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test' |
1497 |
'train' |
67389 |
'validation' |
993 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"concept_set_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"concepts": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
],
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
cs_restaurants
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/cs_restaurants')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_scramble' |
500 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test' |
842 |
'train' |
3569 |
'validation' |
781 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dialog_act": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dialog_act_delexicalized": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target_delexicalized": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
dart
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/dart')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
5097 |
'train' |
62659 |
'validation' |
2768 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dart_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"tripleset": [
[
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
],
"subtree_was_extended": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"target_sources": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
],
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
e2e_nlg
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/e2e_nlg')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_scramble' |
500 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test' |
4693 |
'train' |
33525 |
'validation' |
4299 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"meaning_representation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
totto
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/totto')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_scramble' |
500 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test' |
7700 |
'train' |
121153 |
'validation' |
7700 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"totto_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"table_page_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"table_webpage_url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"table_section_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"table_section_text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"table": [
[
{
"column_span": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"is_header": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"row_span": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"value": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
]
],
"highlighted_cells": [
[
{
"dtype": "int32",
"id": null,
"_type": "Value"
}
]
],
"example_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_annotations": [
{
"original_sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_after_deletion": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_after_ambiguity": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"final_sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
],
"overlap_subset": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
web_nlg_en
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/web_nlg_en')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_numbers' |
500 |
'challenge_test_scramble' |
500 |
'challenge_train_sample' |
502 |
'challenge_validation_sample' |
499 |
'test' |
1779 |
'train' |
35426 |
'validation' |
1667 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"input": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
],
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
],
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"webnlg_id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
web_nlg_ru
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/web_nlg_ru')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_scramble' |
500 |
'challenge_train_sample' |
501 |
'challenge_validation_sample' |
500 |
'test' |
1102 |
'train' |
14630 |
'validation' |
790 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"input": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
],
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
],
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"webnlg_id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
wiki_auto_asset_turk
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/wiki_auto_asset_turk')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_asset_backtranslation' |
359 |
'challenge_test_asset_bfp02' |
359 |
'challenge_test_asset_bfp05' |
359 |
'challenge_test_asset_nopunc' |
359 |
'challenge_test_turk_backtranslation' |
359 |
'challenge_test_turk_bfp02' |
359 |
'challenge_test_turk_bfp05' |
359 |
'challenge_test_turk_nopunc' |
359 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test_asset' |
359 |
'test_turk' |
359 |
'train' |
483801 |
'validation' |
20000 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
schema_guided_dialog
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:gem/schema_guided_dialog')
- 说明：
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.
GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.
It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
- 许可：CC-BY-SA-4.0
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'challenge_test_backtranslation' |
500 |
'challenge_test_bfp02' |
500 |
'challenge_test_bfp05' |
500 |
'challenge_test_nopunc' |
500 |
'challenge_test_scramble' |
500 |
'challenge_train_sample' |
500 |
'challenge_validation_sample' |
500 |
'test' |
10000 |
'train' |
164982 |
'validation' |
10000 |
- 特征：
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dialog_acts": [
{
"act": {
"num_classes": 18,
"names": [
"AFFIRM",
"AFFIRM_INTENT",
"CONFIRM",
"GOODBYE",
"INFORM",
"INFORM_COUNT",
"INFORM_INTENT",
"NEGATE",
"NEGATE_INTENT",
"NOTIFY_FAILURE",
"NOTIFY_SUCCESS",
"OFFER",
"OFFER_INTENT",
"REQUEST",
"REQUEST_ALTS",
"REQ_MORE",
"SELECT",
"THANK_YOU"
],
"id": null,
"_type": "ClassLabel"
},
"slot": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"values": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
],
"context": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
],
"dialog_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"service": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"turn_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"prompt": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}