Riferimenti:
mlsum_de
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/mlsum_de')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'challenge_test_covid' | 5058 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 10695 |
'train' | 220748 |
'validation' | 11392 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/mlsum_es')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'challenge_test_covid' | 1938 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 13366 |
'train' | 259888 |
'validation' | 9977 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_es_en_v0')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 19797 |
'train' | 79515 |
'validation' | 8835 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_ru_en_v0')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 9094 |
'train' | 36898 |
'validation' | 4100 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_tr_en_v0')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 808 |
'train' | 3193 |
'validation' | 355 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_vi_en_v0')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 2167 |
'train' | 9206 |
'validation' | 1023 |
- Caratteristiche :
{
"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_arabo_ar
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_arabic_ar')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 5841 |
'train' | 20441 |
'validation' | 2919 |
- Caratteristiche :
{
"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_cinese_zh
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_chinese_zh')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 3775 |
'train' | 13211 |
'validation' | 1886 |
- Caratteristiche :
{
"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_ceco_cs
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_czech_cs')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 1438 |
'train' | 5033 |
'validation' | 718 |
- Caratteristiche :
{
"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_olandese_nl
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_dutch_nl')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 6248 |
'train' | 21866 |
'validation' | 3123 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_english_en')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 28614 |
'train' | 99020 |
'validation' | 13823 |
- Caratteristiche :
{
"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_francese_fr
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_french_fr')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 12731 |
'train' | 44556 |
'validation' | 6364 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_german_de')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 11669 |
'train' | 40839 |
'validation' | 5833 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_hindi_hi')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 1984 |
'train' | 6942 |
'validation' | 991 |
- Caratteristiche :
{
"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_indonesiano_id
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_indonesian_id')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 9497 |
'train' | 33237 |
'validation' | 4747 |
- Caratteristiche :
{
"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_italiana_it
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_italian_it')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 10189 |
'train' | 35661 |
'validation' | 5093 |
- Caratteristiche :
{
"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_giapponese_ja
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_japanese_ja')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 2530 |
'train' | 8853 |
'validation' | 1264 |
- Caratteristiche :
{
"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_coreano_ko
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_korean_ko')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 2436 |
'train' | 8524 |
'validation' | 1216 |
- Caratteristiche :
{
"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_portoghese_pt
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_portuguese_pt')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 16331 |
'train' | 57159 |
'validation' | 8165 |
- Caratteristiche :
{
"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_russo_ru
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_russian_ru')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 10580 |
'train' | 37028 |
'validation' | 5288 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_spanish_es')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 22632 |
'train' | 79212 |
'validation' | 11316 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_thai_th')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 2950 |
'train' | 10325 |
'validation' | 1475 |
- Caratteristiche :
{
"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_turco_tr
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_turkish_tr')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 900 |
'train' | 3148 |
'validation' | 449 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_vietnamese_vi')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 3917 |
'train' | 13707 |
'validation' | 1957 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/xsum')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'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 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/common_gen')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 1497 |
'train' | 67389 |
'validation' | 993 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/cs_restaurants')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 842 |
'train' | 3569 |
'validation' | 781 |
- Caratteristiche :
{
"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"
}
]
}
dardo
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/dart')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 5097 |
'train' | 62659 |
'validation' | 2768 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/e2e_nlg')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 4693 |
'train' | 33525 |
'validation' | 4299 |
- Caratteristiche :
{
"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"
}
]
}
tutto
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/totto')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 7700 |
'train' | 121153 |
'validation' | 7700 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/web_nlg_en')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'challenge_test_numbers' | 500 |
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 502 |
'challenge_validation_sample' | 499 |
'test' | 1779 |
'train' | 35426 |
'validation' | 1667 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/web_nlg_ru')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 501 |
'challenge_validation_sample' | 500 |
'test' | 1102 |
'train' | 14630 |
'validation' | 790 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/wiki_auto_asset_turk')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'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 |
- Caratteristiche :
{
"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
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:gem/schema_guided_dialog')
- Descrizione :
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.
- Licenza : CC-BY-SA-4.0
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'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 |
- Caratteristiche :
{
"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"
}
]
}