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gem

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_inglese_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_vietnamita_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"
        }
    ]
}