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1
An Error Analysis Framework for Shallow Surface Realisation
In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03159422 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021, 9 ; https://www.aclweb.org/anthology/venues/tacl/ (2021)
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2
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
In: Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021) ; https://hal.archives-ouvertes.fr/hal-03466171 ; Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021), Aug 2021, Online, France. pp.96-120, ⟨10.18653/v1/2021.gem-1.10⟩ (2021)
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3
A Systematic Review of Reproducibility Research in Natural Language Processing
In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume ; https://hal.archives-ouvertes.fr/hal-03466170 ; Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Apr 2021, Online, France. pp.381-393, ⟨10.18653/v1/2021.eacl-main.29⟩ (2021)
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4
Natural Language Generation : From Data Creation to Evaluation via Modelling ; Génération en langue naturelle : de la création des données à l'évaluation, en passant par la modélisation
Shimorina, Anastasia. - : HAL CCSD, 2021
In: https://hal.univ-lorraine.fr/tel-03254708 ; Computation and Language [cs.CL]. Université de Lorraine, 2021. English. ⟨NNT : 2021LORR0080⟩ (2021)
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5
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics ...
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6
An Error Analysis Framework for Shallow Surface Realisation ...
NAACL 2021 2021; Gardent, Claire; Parmentier, Yannick. - : Underline Science Inc., 2021
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7
The 2020 Bilingual, Bi-Directional WebNLG+ Shared Task Overview and Evaluation Results (WebNLG+ 2020)
In: Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+) ; https://hal.archives-ouvertes.fr/hal-03148418 ; Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+), Dec 2020, Dublin/Virtual, Ireland (2020)
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8
Surface Realisation Using Full Delexicalisation
In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) ; 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-02277069 ; 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Nov 2019, Hong Kong, China. pp.3084-3094, ⟨10.18653/v1/D19-1305⟩ (2019)
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9
Can static vocal tract positions represent articulatory targets in continuous speech? Matching static MRI captures against real-time MRI for the French language
In: ICPhS 2019 - International Congress of Phonetic Sciences ; https://hal.inria.fr/hal-02181314 ; ICPhS 2019 - International Congress of Phonetic Sciences, Aug 2019, Melbourne, Australia (2019)
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10
LORIA / Lorraine University at Multilingual Surface Realisation 2019
In: Proceedings of the 2nd Workshop on Multilingual Surface Realisation (MSR 2019) ; https://hal.archives-ouvertes.fr/hal-02459998 ; Proceedings of the 2nd Workshop on Multilingual Surface Realisation (MSR 2019), Nov 2019, Hong Kong, Hong Kong SAR China. pp.88-93, ⟨10.18653/v1/D19-6312⟩ (2019)
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11
Creating a Corpus for Russian Data-to-Text Generation Using Neural Machine Translation and Post-Editing
In: Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-02460000 ; Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing, Aug 2019, Florence, Italy. pp.44-49, ⟨10.18653/v1/W19-3706⟩ (2019)
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12
Handling Rare Items in Data-to-Text Generation
In: Proceedings of the 11th International Conference on Natural Language Generation ; https://hal.archives-ouvertes.fr/hal-02460010 ; Proceedings of the 11th International Conference on Natural Language Generation, Nov 2018, Tilburg University, Netherlands. pp.360-370, ⟨10.18653/v1/W18-6543⟩ (2018)
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13
Split and Rephrase
In: EMNLP 2017: Conference on Empirical Methods in Natural Language Processing ; https://hal.inria.fr/hal-01623746 ; EMNLP 2017: Conference on Empirical Methods in Natural Language Processing, Sep 2017, Copenhagen, Denmark. pp.617 - 627 (2017)
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14
The WebNLG Challenge: Generating Text from RDF Data
In: Proceedings of the 10th International Conference on Natural Language Generation ; https://hal.archives-ouvertes.fr/hal-02461197 ; Proceedings of the 10th International Conference on Natural Language Generation, Sep 2017, Santiago de Compostela, Spain. pp.124-133, ⟨10.18653/v1/W17-3518⟩ (2017)
Abstract: International audience ; The WebNLG challenge consists in mapping sets of RDF triples to text. It provides a common benchmark on which to train, evaluate and compare “microplanners”, i.e. generation systems that verbalise a given content by making a range of complex interacting choices including referring expression generation, aggregation, lexicalisation, surface realisation and sentence segmentation. In this paper, we introduce the microplanning task, describe data preparation, introduce our evaluation methodology, analyse participant results and provide a brief description of the participating systems.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
URL: https://hal.archives-ouvertes.fr/hal-02461197
https://doi.org/10.18653/v1/W17-3518
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15
Creating Training Corpora for NLG Micro-Planning
In: 55th annual meeting of the Association for Computational Linguistics (ACL) ; https://hal.inria.fr/hal-01623744 ; 55th annual meeting of the Association for Computational Linguistics (ACL), Jul 2017, Vancouver, Canada (2017)
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16
Creating Training Corpora For Micro-Planners ...
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17
Creating Training Corpora For Micro-Planners ...
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18
The WebNLG Challenge: Generating Text from RDF Data ...
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The WebNLG Challenge: Generating Text from RDF Data ...
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