gemme

  • Description:

GEM est un environnement de référence pour la génération du langage naturel avec un accent sur l'évaluation, à la fois par des annotations humaines et métriques automatiques.

GEM vise à : (1) mesurer les progrès du NLG à travers 13 ensembles de données couvrant de nombreuses tâches et langues du NLG. (2) fournir une analyse approfondie des données et des modèles présentés via des déclarations de données et des ensembles de défis. (3) développer des normes pour l'évaluation du texte généré à l'aide de mesures automatisées et humaines.

Plus d' informations peuvent être trouvées à https://gem-benchmark.com .

gem/common_gen (configuration par défaut)

  • Description Config: CommonGen est une tâche de génération de texte contraint, associé à un ensemble de données de référence, aux machines d'essai explicitement la capacité de raisonnement de bon sens générative. Étant donné un ensemble de concepts communs ; la tâche consiste à générer une phrase cohérente décrivant un scénario quotidien en utilisant ces concepts.

  • Taille du téléchargement: 1.84 MiB

  • Dataset Taille: 16.84 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 1 497
'train' 67 389
'validation' 993
  • Caractéristiques:
FeaturesDict({
    'concept_set_id': tf.int32,
    'concepts': Sequence(tf.string),
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'target': tf.string,
})
  • citation:
@inproceedings{lin2020commongen,
  title = "CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning",
  author = "Lin, Bill Yuchen  and
    Zhou, Wangchunshu  and
    Shen, Ming  and
    Zhou, Pei  and
    Bhagavatula, Chandra  and
    Choi, Yejin  and
    Ren, Xiang",
  booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
  month = nov,
  year = "2020",
  address = "Online",
  publisher = "Association for Computational Linguistics",
  url = "https://www.aclweb.org/anthology/2020.findings-emnlp.165",
  pages = "1823--1840",
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/cs_restaurants

  • Description Config: La tâche génère des réponses dans le cadre d'un système de dialogue (hypothétique) qui fournit des informations sur les restaurants. L'entrée est un type d'acte d'intention/dialogue de base et une liste d'emplacements (attributs) et leurs valeurs. La sortie est une phrase en langage naturel.

  • Taille du téléchargement: 1.46 MiB

  • Dataset Taille: 2.71 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 842
'train' 3 569
'validation' 781
  • Caractéristiques:
FeaturesDict({
    'dialog_act': tf.string,
    'dialog_act_delexicalized': tf.string,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'target': tf.string,
    'target_delexicalized': tf.string,
})
  • citation:
@inproceedings{cs_restaurants,
  address = {Tokyo, Japan},
  title = {Neural {Generation} for {Czech}: {Data} and {Baselines} },
  shorttitle = {Neural {Generation} for {Czech} },
  url = {https://www.aclweb.org/anthology/W19-8670/},
  urldate = {2019-10-18},
  booktitle = {Proceedings of the 12th {International} {Conference} on {Natural} {Language} {Generation} ({INLG} 2019)},
  author = {Dušek, Ondřej and Jurčíček, Filip},
  month = oct,
  year = {2019},
  pages = {563--574}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gemme/fléchette

  • Description Config: DART est un grand domaine ouvert structuré corpus d' enregistrer des données de génération de texte avec des annotations de phrases de haute qualité à chaque entrée étant un ensemble de triplets relation d'entité suite à une structure arbre ontologie.

  • Taille du téléchargement: 28.01 MiB

  • Dataset Taille: 33.78 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'test' 6 959
'train' 62 659
'validation' 2 768
  • Caractéristiques:
FeaturesDict({
    'dart_id': tf.int32,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'subtree_was_extended': tf.bool,
    'target': tf.string,
    'target_sources': Sequence(tf.string),
    'tripleset': Sequence(tf.string),
})
  • citation:
@article{radev2020dart,
  title=Dart: Open-domain structured data record to text generation,
  author={Radev, Dragomir and Zhang, Rui and Rau, Amrit and Sivaprasad, Abhinand and Hsieh, Chiachun and Rajani, Nazneen Fatema and Tang, Xiangru and Vyas, Aadit and Verma, Neha and Krishna, Pranav and others},
  journal={arXiv preprint arXiv:2007.02871},
  year={2020}
}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/e2e_nlg

  • Description Config: Le jeu de données E2E est conçu pour une tâche domaine limité des données à texte - génération de descriptions de restaurants / recommandations basées sur jusqu'à 8 attributs différents (nom, région, gamme de prix , etc.)

  • Taille du téléchargement: 13.99 MiB

  • Dataset Taille: 16.92 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 4 693
'train' 33 525
'validation' 4 299
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'meaning_representation': tf.string,
    'references': Sequence(tf.string),
    'target': tf.string,
})
  • citation:
@inproceedings{e2e_cleaned,
  address = {Tokyo, Japan},
  title = {Semantic {Noise} {Matters} for {Neural} {Natural} {Language} {Generation} },
  url = {https://www.aclweb.org/anthology/W19-8652/},
  booktitle = {Proceedings of the 12th {International} {Conference} on {Natural} {Language} {Generation} ({INLG} 2019)},
  author = {Dušek, Ondřej and Howcroft, David M and Rieser, Verena},
  year = {2019},
  pages = {421--426},
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/mlsum_de

  • Description Config: MLSum est une grande échelle de jeu de données Multilingual summarization. Il est construit à partir de médias en ligne, cette division se concentrant sur l'allemand.

  • Taille du téléchargement: 345.98 MiB

  • Dataset Taille: 963.60 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'challenge_test_covid' 5 058
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 10 695
'train' 220 748
'validation' 11 392
  • Caractéristiques:
FeaturesDict({
    'date': tf.string,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'target': tf.string,
    'text': tf.string,
    'title': tf.string,
    'topic': tf.string,
    'url': tf.string,
})
  • citation:
@inproceedings{scialom-etal-2020-mlsum,
    title = "{MLSUM}: The Multilingual Summarization Corpus",
    author = {Scialom, Thomas  and Dray, Paul-Alexis  and Lamprier, Sylvain  and Piwowarski, Benjamin  and Staiano, Jacopo},
    booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
    year = {2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/mlsum_es

  • Description Config: MLSum est une grande échelle de jeu de données Multilingual summarization. Il est construit à partir de médias en ligne, cette division se concentrant sur l'espagnol.

  • Taille du téléchargement: 501.27 MiB

  • Taille Dataset: 1.29 GiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'challenge_test_covid' 1 938
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 13 366
'train' 259 888
'validation' 9 977
  • Caractéristiques:
FeaturesDict({
    'date': tf.string,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'target': tf.string,
    'text': tf.string,
    'title': tf.string,
    'topic': tf.string,
    'url': tf.string,
})
  • citation:
@inproceedings{scialom-etal-2020-mlsum,
    title = "{MLSUM}: The Multilingual Summarization Corpus",
    author = {Scialom, Thomas  and Dray, Paul-Alexis  and Lamprier, Sylvain  and Piwowarski, Benjamin  and Staiano, Jacopo},
    booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
    year = {2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/schema_guided_dialog

  • Description Config: Le jeu de données de dialogue Schéma-guidée (SGD) contient 18K dialogues axés sur les tâches multi-domaines entre un humain et un assistant virtuel, qui couvre 17 domaines allant des banques et des événements aux médias, calendrier, Voyage, et la météo.

  • Taille du téléchargement: 17.00 MiB

  • Dataset Taille: 201.19 MiB

  • Auto-cache ( documentation ): Oui (challenge_test_backtranslation, challenge_test_bfp02, challenge_test_bfp05, challenge_test_nopunc, challenge_test_scramble, challenge_train_sample, challenge_validation_sample, test, validation), seulement quand shuffle_files=False (train)

  • scissions:

Diviser Exemples
'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' 10 000
'train' 164 982
'validation' 10 000
  • Caractéristiques:
FeaturesDict({
    'context': Sequence(tf.string),
    'dialog_acts': Sequence({
        'act': ClassLabel(shape=(), dtype=tf.int64, num_classes=18),
        'slot': tf.string,
        'values': Sequence(tf.string),
    }),
    'dialog_id': tf.string,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'prompt': tf.string,
    'references': Sequence(tf.string),
    'service': tf.string,
    'target': tf.string,
    'turn_id': tf.int32,
})
  • citation:
@article{rastogi2019towards,
  title={Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset},
  author={Rastogi, Abhinav and Zang, Xiaoxue and Sunkara, Srinivas and Gupta, Raghav and Khaitan, Pranav},
  journal={arXiv preprint arXiv:1909.05855},
  year={2019}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gemme/totto

  • Description Config: Totto est une table à texte tâche NLG. La tâche est la suivante : Étant donné un tableau Wikipédia avec des noms de lignes, des noms de colonnes et des cellules de tableau, avec un sous-ensemble de cellules en surbrillance, générer une description en langage naturel pour la partie en surbrillance du tableau.

  • Taille du téléchargement: 180.75 MiB

  • Dataset Taille: 645.86 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 7 700
'train' 121 153
'validation' 7 700
  • Caractéristiques:
FeaturesDict({
    'example_id': tf.string,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'highlighted_cells': Sequence(Sequence(tf.int32)),
    'overlap_subset': tf.string,
    'references': Sequence(tf.string),
    'sentence_annotations': Sequence({
        'final_sentence': tf.string,
        'original_sentence': tf.string,
        'sentence_after_ambiguity': tf.string,
        'sentence_after_deletion': tf.string,
    }),
    'table': Sequence(Sequence({
        'column_span': tf.int32,
        'is_header': tf.bool,
        'row_span': tf.int32,
        'value': tf.string,
    })),
    'table_page_title': tf.string,
    'table_section_text': tf.string,
    'table_section_title': tf.string,
    'table_webpage_url': tf.string,
    'target': tf.string,
    'totto_id': tf.int32,
})
  • citation:
@inproceedings{parikh2020totto,
  title=ToTTo: A Controlled Table-To-Text Generation Dataset,
  author={Parikh, Ankur and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},
  booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  pages={1173--1186},
  year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/web_nlg_fr

  • Description Config: WebNLG est un ensemble de données bilingue (anglais, russe) de DBpedia parallèles ensembles triples et des textes courts qui couvrent environ 450 différentes propriétés de DBpedia. Les données WebNLG ont été créées à l'origine pour promouvoir le développement de verbalisateurs RDF capables de générer des textes courts et de gérer la micro-planification.

  • Taille du téléchargement: 12.57 MiB

  • Dataset Taille: 19.91 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'challenge_test_numbers' 500
'challenge_test_scramble' 500
'challenge_train_sample' 502
'challenge_validation_sample' 499
'test' 1 779
'train' 35 426
'validation' 1 667
  • Caractéristiques:
FeaturesDict({
    'category': tf.string,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'input': Sequence(tf.string),
    'references': Sequence(tf.string),
    'target': tf.string,
    'webnlg_id': tf.string,
})
  • citation:
@inproceedings{gardent2017creating,
  author =  "Gardent, Claire
    and Shimorina, Anastasia
    and Narayan, Shashi
    and Perez-Beltrachini, Laura",
  title =   "Creating Training Corpora for NLG Micro-Planners",
  booktitle =   "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
  year =    "2017",
  publisher =   "Association for Computational Linguistics",
  pages =   "179--188",
  location =    "Vancouver, Canada",
  doi =     "10.18653/v1/P17-1017",
  url =     "http://www.aclweb.org/anthology/P17-1017"
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/web_nlg_ru

  • Description Config: WebNLG est un ensemble de données bilingue (anglais, russe) de DBpedia parallèles ensembles triples et des textes courts qui couvrent environ 450 différentes propriétés de DBpedia. Les données WebNLG ont été créées à l'origine pour promouvoir le développement de verbalisateurs RDF capables de générer des textes courts et de gérer la micro-planification.

  • Taille du téléchargement: 7.49 MiB

  • Dataset Taille: 11.30 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 501
'challenge_validation_sample' 500
'test' 1 102
'train' 14 630
'validation' 790
  • Caractéristiques:
FeaturesDict({
    'category': tf.string,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'input': Sequence(tf.string),
    'references': Sequence(tf.string),
    'target': tf.string,
    'webnlg_id': tf.string,
})
  • citation:
@inproceedings{gardent2017creating,
  author =  "Gardent, Claire
    and Shimorina, Anastasia
    and Narayan, Shashi
    and Perez-Beltrachini, Laura",
  title =   "Creating Training Corpora for NLG Micro-Planners",
  booktitle =   "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
  year =    "2017",
  publisher =   "Association for Computational Linguistics",
  pages =   "179--188",
  location =    "Vancouver, Canada",
  doi =     "10.18653/v1/P17-1017",
  url =     "http://www.aclweb.org/anthology/P17-1017"
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_auto_asset_turk

  • Description Config: WikiAuto fournit un ensemble de phrases alignées de Wikipédia en anglais et simple Wikipédia en anglais comme ressource pour former des systèmes de simplification de la phrase. ASSET et TURK sont des ensembles de données de simplification de haute qualité utilisés pour les tests.

  • Taille du téléchargement: 121.01 MiB

  • Dataset Taille: 202.40 MiB

  • Auto-cache ( documentation ): Oui (challenge_test_asset_backtranslation, challenge_test_asset_bfp02, challenge_test_asset_bfp05, challenge_test_asset_nopunc, challenge_test_turk_backtranslation, challenge_test_turk_bfp02, challenge_test_turk_bfp05, challenge_test_turk_nopunc, challenge_train_sample, challenge_validation_sample, test_asset, test_turk, validation), seulement quand shuffle_files=False (train)

  • scissions:

Diviser Exemples
'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' 483 801
'validation' 20 000
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'target': tf.string,
})
  • citation:
@inproceedings{jiang-etal-2020-neural,
    title = "Neural {CRF} Model for Sentence Alignment in Text Simplification",
    author = "Jiang, Chao  and
      Maddela, Mounica  and
      Lan, Wuwei  and
      Zhong, Yang  and
      Xu, Wei",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.acl-main.709",
    doi = "10.18653/v1/2020.acl-main.709",
    pages = "7943--7960",
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gemme/xsomme

  • Description Config: L'ensemble de données est la tâche de summarization abstractive sous sa forme extrême, son résumé au sujet d' un document en une seule phrase.

  • Taille du téléchargement: 246.31 MiB

  • Dataset Taille: 78.89 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'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' 1 166
'train' 23 206
'validation' 1 117
  • Caractéristiques:
FeaturesDict({
    'document': tf.string,
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'target': tf.string,
    'xsum_id': tf.string,
})
  • citation:
@inproceedings{Narayan2018dont,
  author = "Shashi Narayan and Shay B. Cohen and Mirella Lapata",
  title = "Don't Give Me the Details, Just the Summary! {T}opic-Aware Convolutional Neural Networks for Extreme Summarization",
  booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing ",
  year = "2018",
  address = "Brussels, Belgium",
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_arabic_ar

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 56.25 MiB

  • Dataset Taille: 291.42 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 5 841
'train' 20 441
'validation' 2 919
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'ar': Text(shape=(), dtype=tf.string),
        'en': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'ar': Text(shape=(), dtype=tf.string),
        'en': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_chinois_zh

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 31.38 MiB

  • Dataset Taille: 122.06 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'test' 3 775
'train' 13 211
'validation' 1 886
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'zh': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'zh': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_czech_cs

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 13.84 MiB

  • Dataset Taille: 58.05 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'test' 1 438
'train' 5 033
'validation' 718
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'cs': Text(shape=(), dtype=tf.string),
        'en': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'cs': Text(shape=(), dtype=tf.string),
        'en': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_dutch_nl

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 53.88 MiB

  • Dataset Taille: 237.97 MiB

  • Auto-cache ( documentation ): Oui (test, validation), seulement quand shuffle_files=False (train)

  • scissions:

Diviser Exemples
'test' 6 248
'train' 21 866
'validation' 3 123
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'nl': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'nl': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_english_fr

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 112.56 MiB

  • Dataset Taille: 657.51 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 28 614
'train' 99 020
'validation' 13 823
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_french_fr

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 113.26 MiB

  • Dataset Taille: 522.28 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 12 731
'train' 44 556
'validation' 6 364
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'fr': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'fr': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_german_de

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 102.65 MiB

  • Dataset Taille: 452.46 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 11 669
'train' 40 839
'validation' 5 833
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'de': Text(shape=(), dtype=tf.string),
        'en': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'de': Text(shape=(), dtype=tf.string),
        'en': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_hindi_hi

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 20.07 MiB

  • Dataset Taille: 138.06 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'test' 1 984
'train' 6 942
'validation' 991
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'hi': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'hi': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_indonesian_id

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 80.08 MiB

  • Dataset Taille: 370.63 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 9 497
'train' 33 237
'validation' 4 747
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'id': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'id': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_italian_it

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 84.80 MiB

  • Dataset Taille: 374.40 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 10 189
'train' 35 661
'validation' 5 093
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'it': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'it': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_japanese_ja

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 21.75 MiB

  • Dataset Taille: 103.19 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'test' 2 530
'train' 8 853
'validation' 1 264
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'ja': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'ja': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_korean_ko

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 22.26 MiB

  • Dataset Taille: 102.35 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'test' 2 436
'train' 8 524
'validation' 1 216
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'ko': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'ko': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_portuguese_pt

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 131.17 MiB

  • Dataset Taille: 570.46 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 16 331
'train' 57 159
'validation' 8 165
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'pt': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'pt': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_russian_ru

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 101.36 MiB

  • Dataset Taille: 564.69 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 10 580
'train' 37 028
'validation' 5 288
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'ru': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'ru': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_spanish_es

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 189.06 MiB

  • Dataset Taille: 849.75 MiB

  • Mis en cache automatique ( documentation ): Non

  • scissions:

Diviser Exemples
'test' 22 632
'train' 79 212
'validation' 11 316
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'es': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'es': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_thai_th

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 28.60 MiB

  • Dataset Taille: 193.77 MiB

  • Auto-cache ( documentation ): Oui (test, validation), seulement quand shuffle_files=False (train)

  • scissions:

Diviser Exemples
'test' 2 950
'train' 10 325
'validation' 1 475
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'th': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'th': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_turkish_tr

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 6.73 MiB

  • Dataset Taille: 30.75 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'test' 900
'train' 3 148
'validation' 449
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'tr': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'tr': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."

gem/wiki_lingua_vietnamese_vi

  • Description Config: Wikilingua est une grande échelle, ensemble de données multilingues pour l'évaluation des systèmes de résumé abstractive translinguistique ..

  • Taille du téléchargement: 36.27 MiB

  • Dataset Taille: 179.77 MiB

  • Auto-cache ( documentation ): Oui

  • scissions:

Diviser Exemples
'test' 3 917
'train' 13 707
'validation' 1 957
  • Caractéristiques:
FeaturesDict({
    'gem_id': tf.string,
    'gem_parent_id': tf.string,
    'references': Sequence(tf.string),
    'source': tf.string,
    'source_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'vi': Text(shape=(), dtype=tf.string),
    }),
    'target': tf.string,
    'target_aligned': Translation({
        'en': Text(shape=(), dtype=tf.string),
        'vi': Text(shape=(), dtype=tf.string),
    }),
})
  • citation:
@inproceedings{ladhak-wiki-2020,
title=WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization,
author={Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
booktitle={Findings of EMNLP, 2020},
year={2020}
}
@article{gehrmann2021gem,
  author    = {Sebastian Gehrmann and
               Tosin P. Adewumi and
               Karmanya Aggarwal and
               Pawan Sasanka Ammanamanchi and
               Aremu Anuoluwapo and
               Antoine Bosselut and
               Khyathi Raghavi Chandu and
               Miruna{-}Adriana Clinciu and
               Dipanjan Das and
               Kaustubh D. Dhole and
               Wanyu Du and
               Esin Durmus and
               Ondrej Dusek and
               Chris Emezue and
               Varun Gangal and
               Cristina Garbacea and
               Tatsunori Hashimoto and
               Yufang Hou and
               Yacine Jernite and
               Harsh Jhamtani and
               Yangfeng Ji and
               Shailza Jolly and
               Dhruv Kumar and
               Faisal Ladhak and
               Aman Madaan and
               Mounica Maddela and
               Khyati Mahajan and
               Saad Mahamood and
               Bodhisattwa Prasad Majumder and
               Pedro Henrique Martins and
               Angelina McMillan{-}Major and
               Simon Mille and
               Emiel van Miltenburg and
               Moin Nadeem and
               Shashi Narayan and
               Vitaly Nikolaev and
               Rubungo Andre Niyongabo and
               Salomey Osei and
               Ankur P. Parikh and
               Laura Perez{-}Beltrachini and
               Niranjan Ramesh Rao and
               Vikas Raunak and
               Juan Diego Rodriguez and
               Sashank Santhanam and
               Jo{\~{a} }o Sedoc and
               Thibault Sellam and
               Samira Shaikh and
               Anastasia Shimorina and
               Marco Antonio Sobrevilla Cabezudo and
               Hendrik Strobelt and
               Nishant Subramani and
               Wei Xu and
               Diyi Yang and
               Akhila Yerukola and
               Jiawei Zhou},
  title     = {The {GEM} Benchmark: Natural Language Generation, its Evaluation and
               Metrics},
  journal   = {CoRR},
  volume    = {abs/2102.01672},
  year      = {2021},
  url       = {https://arxiv.org/abs/2102.01672},
  archivePrefix = {arXiv},
  eprint    = {2102.01672}
}

Note that each GEM dataset has its own citation. Please see the source to see
the correct citation for each contained dataset."