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Linguistic Analysis and Automatic Information Extraction of Semantic Relations in Arabic ; Analyse linguistique et extraction automatique de relations sémantiques des textes en arabe
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In: https://hal.archives-ouvertes.fr/tel-03572307 ; Linguistique. Université Bourgogne Franche-Comté, 2020. Français (2020)
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Abstract:
This thesis focuses on the development of a tool for the automatic processing of Modern Standard Arabic, at the morphological and semanticlevels, with the final objective of Information Extraction on technological innovations. As far as the morphological analysis is concerned, our tool includes several successive processing stages that allow to label and disambiguate occurrences in texts : a morphological layer (Gibran 1.0), which relies on Arabic pattern as distinctive features ; a contextual layer (Gibran 2.0), which uses contextual rules ; and a third layer (Gibran 3.0), which uses a machine learning model. Our methodology is evaluated using the annotated corpus Arabic-PADT UD treebank. The evaluations obtain an F-measure of 0.92 and 0.90 for the morphological analyses. These experiments demontrate the possibility of improving such a corpus through linguistic analyses. This approach allowed us to develop a prototype of information extraction on technological innovations for the Arabic language. It is based on the morphological analysis and syntaxico-semantic patterns. This thesis is part of a doctoral-entrepreneurial course. ; Cette recherche porte sur le développement d’un outil de traitement automatique de la langue arabe standard moderne, au niveau morphologique et sémantique, avec comme objectif final l’extraction d’information dans le domaine de l’innovation technologique en entreprise. En ce qui concerne l’analyse morphologique, notre outil comprend plusieurs traitements successifs qui permettent d’étiqueter et de désambiguïser les occurrences dans les textes : une couche morphologique (Gibran 1.0), qui s’appuie sur les schèmes arabes commetraits distinctifs ; une couche contextuelle (Gibran 2.0), qui fait appel à des règles contextuelles ; et une troisième couche (Gibran 3.0) qui fait appel à un modèle d’apprentissage automatique. Notre méthodologie est évaluée sur le corpus annoté Arabic-PADT UD treebank. Les évaluations obtiennent une F-mesure de 0,92 et 0,90 pour les analyses morphologiques. Ces expérimentations montrent, entre autres, la possibilité d’améliorer une telle ressource par les analyses linguistiques. Cette approche nous a permis de développer un prototype d’extrac-tion d’information autour de l’innovation technologique pour la langue arabe. Il s’appuie sur l’analyse morphologique et des patrons syntaxico-sémantiques. Cette thèse s’inscrit dans un parcours docteur-entrepreneur.
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Keyword:
[INFO]Computer Science [cs]; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; Analyse linguistique; arabe standard moderne; Arabic language; Arabic-PADT UD treebank; en- treprise; étiquetage morphologique; extraction d’information; Information extraction; langue arabe; Linguistic analysis; Modern Standard Arabic; morphologie; morphology; pattern; POS tagging; schème; start-up
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URL: https://hal.archives-ouvertes.fr/tel-03572307
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Representation and Parsing of Multiword Expressions ; Representation and Parsing of Multiword Expressions: Current trends
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In: https://hal.archives-ouvertes.fr/hal-01537920 ; Yannick Parmentier; Jakub Waszczuk. Germany. 3, Language Science Press, 2019, Phraseology and Multiword Expressions ; http://langsci-press.org (2019)
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CoNLL 2018 Shared Task - UDPipe Baseline Models and Supplementary Materials
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Straka, Milan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2018
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Discovering syntactic phenomena with and within precision grammars
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CoNLL 2017 Shared Task - UDPipe Baseline Models and Supplementary Materials
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Straka, Milan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2017
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Modelado de gramáticas basadas en dependencias a partir de un treebank de constituyentes
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Phrase extraction and rescoring in statistical machine translation
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Srivastava, Ankit Kumar. - : Dublin City University. Centre for Next Generation Localisation (CNGL), 2014. : Dublin City University. School of Computing, 2014
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In: Srivastava, Ankit Kumar (2014) Phrase extraction and rescoring in statistical machine translation. PhD thesis, Dublin City University. (2014)
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Building Computational Resources : The URDU.KON-TB Treebank and the Urdu Parser
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Treebank-Based Deep Grammar Acquisition for French Probabilistic Parsing Resources
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Schluter, Natalie. - : Dublin City University. National Centre for Language Technology (NCLT), 2011. : Dublin City University. School of Computing, 2011
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In: Schluter, Natalie (2011) Treebank-Based Deep Grammar Acquisition for French Probabilistic Parsing Resources. PhD thesis, Dublin City University. (2011)
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Treebank-based automatic acquisition of wide coverage, deep linguistic resources for Japanese
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Oya, Masanori. - : Dublin City University. National Centre for Language Technology (NCLT), 2010. : Dublin City University. School of Computing, 2010
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In: Oya, Masanori (2010) Treebank-based automatic acquisition of wide coverage, deep linguistic resources for Japanese. Master of Science thesis, Dublin City University. (2010)
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Treebank-based acquisition of Chinese LFG resources for parsing and generation
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Guo, Yuqing. - : Dublin City University. School of Computing, 2009
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In: Guo, Yuqing (2009) Treebank-based acquisition of Chinese LFG resources for parsing and generation. PhD thesis, Dublin City University. (2009)
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Parsing with automatically acquired, wide-coverage, robust, probabilistic LFG approximations
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Cahill, Aoife. - : Dublin City University. School of Computing, 2004
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In: Cahill, Aoife orcid:0000-0002-3519-7726 (2004) Parsing with automatically acquired, wide-coverage, robust, probabilistic LFG approximations. PhD thesis, Dublin City University. (2004)
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