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Corpus-based Language Universals Analysis using Universal Dependencies ; Analyse orientée corpus d'universaux linguistiques sur Universal Dependencies
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In: SyntaxFest Quasy 2021 - Quantitative Syntax ; https://hal.inria.fr/hal-03501774 ; SyntaxFest Quasy 2021 - Quantitative Syntax, Mar 2022, Sofia, Bulgaria (2022)
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Corpus-based Language Universals Analysis using Universal Dependencies ; Analyse orientée corpus d'universaux linguistiques sur Universal Dependencies
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In: Quasy (Quantitative Syntax), SyntaxFest 2021 ; https://hal.inria.fr/hal-03501774 ; Quasy (Quantitative Syntax), SyntaxFest 2021, Mar 2022, Sofia, Bulgaria (2022)
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Starting a new treebank? Go SUD! Theoretical and practical benefits of the Surface-Syntactic distributional approach
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In: Sixth International Conference on Dependency Linguistics (Depling, SyntaxFest 2021) ; https://hal.inria.fr/hal-03509136 ; Sixth International Conference on Dependency Linguistics (Depling, SyntaxFest 2021), Mar 2022, Sofia, Bulgaria (2022)
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A morph-based and a word-based treebank for Beja
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In: SyntaxFest ; TLT 2021 - 20th International Workshop on Treebanks and Linguistic Theories ; https://hal.archives-ouvertes.fr/hal-03494462 ; TLT 2021 - 20th International Workshop on Treebanks and Linguistic Theories, Mar 2022, Sofia, Bulgaria (2022)
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Convertir le Trésor de la Langue Française en Ontolex-Lemon : un zeste de données liées
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In: Journées LIFT 2021 - Linguistique informatique, formelle et de terrain ; https://hal.inria.fr/hal-03463294 ; Journées LIFT 2021 - Linguistique informatique, formelle et de terrain, Dec 2021, Grenoble, France (2021)
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A morph-based and a word-based treebank for Beja
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In: SyntaxFest ; https://hal.archives-ouvertes.fr/hal-03494462 ; SyntaxFest, In press (2021)
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Analyse orientée corpus d'universaux de Greenberg sur Universal Dependencies
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In: Journées LIFT 2021 - Linguistique informatique, formelle et de terrain ; https://hal.inria.fr/hal-03462112 ; Journées LIFT 2021 - Linguistique informatique, formelle et de terrain, GDR LIFT - Linguistique Informatique, Formelle et de Terrain, Dec 2021, Grenoble, France (2021)
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Graph Matching and Graph Rewriting: GREW tools for corpus exploration, maintenance and conversion
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In: EACL 2021 - 16th conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03177701 ; EACL 2021 - 16th conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kiev/Online, Ukraine ; https://2021.eacl.org/ (2021)
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Convertir le Trésor de la Langue Française en Ontolex-Lemon : un zeste de données liées ...
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Convertir le Trésor de la Langue Française en Ontolex-Lemon : un zeste de données liées ...
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A French corpus annotated for multiword expressions and named entities
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In: ISSN: 2299-856X ; EISSN: 2299-8470 ; Journal of Language Modelling ; https://hal.archives-ouvertes.fr/hal-03016721 ; Journal of Language Modelling, Institute of Computer Science, Polish Academy of Sciences, Poland, 2020, 8 (2), pp.415-479. ⟨10.15398/jlm.v8i2.265⟩ (2020)
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Edition 1.2 of the PARSEME Shared Task on Semi-supervised Identification of Verbal Multiword Expressions
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In: Joint Workshop on Multiword Expressions and Electronic Lexicons (MWE-LEX 2020) ; https://hal.archives-ouvertes.fr/hal-03014927 ; Joint Workshop on Multiword Expressions and Electronic Lexicons (MWE-LEX 2020), 2020, Barcelona, Spain ; https://www.aclweb.org/anthology/volumes/2020.mwe-1/ (2020)
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When Collaborative Treebank Curation Meets Graph Grammars ; When Collaborative Treebank Curation Meets Graph Grammars: Arborator With a Grew Back-End
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In: LREC 2020 - 12th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-03021720 ; LREC 2020 - 12th Language Resources and Evaluation Conference, May 2020, Marseille, France ; http://www.lrec-conf.org/proceedings/lrec2020/index.html (2020)
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A French Version of the FraCaS Test Suite ; Une version française de la ressource FraCaS
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In: LREC 2020 - Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-02619239 ; LREC 2020 - Language Resources and Evaluation Conference, May 2020, Marseille, France. pp.9 (2020)
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Morpho-syntactically annotated corpora provided for the PARSEME Shared Task on Semi-Supervised Identification of Verbal Multiword Expressions (edition 1.2)
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Guillaume, Bruno; Ramisch, Carlos; Waszczuk, Jakub; Monti, Johanna; Di Buono, Maria Pia; Sangati, Federico; Speranza, Giulia; Carlino, Carola; Güngör, Tunga; Yirmibeşoğlu, Zeynep; Sak, Haşim; Saraçlar, Murat; Giouli, Voula; Foufi, Vassiliki; Ramisch, Renata; Rademaker, Alexandre; Vale, Oto; Wilkens, Rodrigo; Candito, Marie; Crabbé, Benoît; Segonne, Vincent; Liebeskind, Chaya; Stymne, Sara; Hajič, Jan; Ginter, Filip; Luotolahti, Juhani; Straka, Milan; Zeman, Daniel; Barbu Mititelu, Verginica; Cristescu, Mihaela; Vaidya, Ashwini; Bhatia, Archna; Lichte, Timm; Ehren, Rafael; Jiang, Menghan; Xu, Hongzhi; Walsh, Abigail; Irimia, Elena; Dowling, Meghan. - : PARSEME, 2020
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Abstract:
This multilingual resource contains corpora for 14 languages, gathered at the occasion of the 1.2 edition of the PARSEME Shared Task on semi-supervised Identification of Verbal MWEs (2020). These corpora were meant to serve as additional "raw" corpora, to help discovering unseen verbal MWEs. The corpora are provided in CONLL-U (https://universaldependencies.org/format.html) format. They contain morphosyntactic annotations (parts of speech, lemmas, morphological features, and syntactic dependencies). Depending on the language, the information comes from treebanks (mostly Universal Dependencies v2.x) or from automatic parsers trained on UD v2.x treebanks (e.g., UDPipe). VMWEs include idioms (let the cat out of the bag), light-verb constructions (make a decision), verb-particle constructions (give up), inherently reflexive verbs (help oneself), and multi-verb constructions (make do). For the 1.2 shared task edition, the data covers 14 languages, for which VMWEs were annotated according to the universal guidelines. The corpora are provided in the cupt format, inspired by the CONLL-U format. Morphological and syntactic information – not necessarily using UD tagsets – including parts of speech, lemmas, morphological features and/or syntactic dependencies are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). This item contains training, development and test data, as well as the evaluation tools used in the PARSEME Shared Task 1.2 (2020). The annotation guidelines are available online: http://parsemefr.lif.univ-mrs.fr/parseme-st-guidelines/1.2
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Keyword:
dependency trees; morphological analysis; morphosyntactic annotation
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URL: http://hdl.handle.net/11234/1-3416
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