Textual Entailment and Rewriting
Identifieur interne : 004A80 ( Hal/Corpus ); précédent : 004A79; suivant : 004A81Textual Entailment and Rewriting
Auteurs : Paul BedarideSource :
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Abstract
This thesis presents several contributions on the theme of recognising textual entailment (RTE). The RTE is the human capacity, given two texts, to determine whether the meaning of the second text could be deduced from the meaning of the first or not. One of the contributions made to the field is a hybrid system of RTE taking analysis of an existing stochastic parser to label them with semantics roles, then turning obtained structures in logical formulas using rewrite rules to finally test the entailment using proof tools. Another contribution of this thesis is the generation of finely annotated tests suites with a uniform distribution of phenomena coupled with a new methodology of systems evaluation using error minning techniques developed by the community of parsing allowing better identification of systems limitations. For this, we create a set of formulas, then we generate annotated syntactics realisations corresponding by using an existing generation system. Then, we test whether or not there is an entailment between each pair of possible syntactics realisations. Finally, we select a subset of this set of problems of a given size and a satisfactory a certain number of constraints using an algorithm that we developed.
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The RTE is the human capacity, given two texts, to determine whether the meaning of the second text could be deduced from the meaning of the first or not. One of the contributions made to the field is a hybrid system of RTE taking analysis of an existing stochastic parser to label them with semantics roles, then turning obtained structures in logical formulas using rewrite rules to finally test the entailment using proof tools. Another contribution of this thesis is the generation of finely annotated tests suites with a uniform distribution of phenomena coupled with a new methodology of systems evaluation using error minning techniques developed by the community of parsing allowing better identification of systems limitations. For this, we create a set of formulas, then we generate annotated syntactics realisations corresponding by using an existing generation system. Then, we test whether or not there is an entailment between each pair of possible syntactics realisations. Finally, we select a subset of this set of problems of a given size and a satisfactory a certain number of constraints using an algorithm that we developed.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Textual Entailment and Rewriting</title><title xml:lang="fr">Implication Textuelle et Réécriture</title><author role="aut"><persName><forename type="first">Paul</forename><surname>Bedaride</surname></persName><email>paul.bedaride@gmail.com</email><idno type="halauthor">552902</idno><affiliation ref="#struct-35123"></affiliation></author><editor role="depositor"><persName><forename>Paul</forename><surname>Bedaride</surname></persName><email>paul.bedaride@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2010-11-30 20:14:56</date><date type="whenModified">2015-09-22 01:13:12</date><date type="whenReleased">2010-12-02 14:39:23</date><date type="whenProduced">2010-10-18</date><date type="whenEndEmbargoed">2010-11-30</date><ref type="file" target="https://tel.archives-ouvertes.fr/tel-00541581/document"><date notBefore="2010-11-30"></date></ref><ref type="file" n="1" target="https://tel.archives-ouvertes.fr/tel-00541581/file/these.pdf"><date notBefore="2010-11-30"></date></ref></edition><respStmt><resp>contributor</resp><name key="115194"><persName><forename>Paul</forename><surname>Bedaride</surname></persName><email>paul.bedaride@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">tel-00541581</idno><idno type="halUri">https://tel.archives-ouvertes.fr/tel-00541581</idno><idno type="halBibtex">bedaride:tel-00541581</idno><idno type="halRefHtml">Autre [cs.OH]. Université Henri Poincaré - Nancy I, 2010. Français</idno><idno type="halRef">Autre [cs.OH]. Université Henri Poincaré - Nancy I, 2010. Français</idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="INRIA_TEST">INRIA - Institut National de Recherche en Informatique et en Automatique</idno></seriesStmt><notesStmt></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Textual Entailment and Rewriting</title><title xml:lang="fr">Implication Textuelle et Réécriture</title><author role="aut"><persName><forename type="first">Paul</forename><surname>Bedaride</surname></persName><email>paul.bedaride@gmail.com</email><idno type="halAuthorId">552902</idno><affiliation ref="#struct-35123"></affiliation></author></analytic><monogr><imprint><date type="dateDefended">2010-10-18</date></imprint><authority type="institution">Université Henri Poincaré - Nancy I</authority><authority type="school">IAEM Lorraine</authority><authority type="supervisor">Claire Gardent(gardent@loria.fr)</authority><authority type="jury">Philippe Blache (rapporteur)</authority><authority type="jury">Patrick Saint-Dizier (rapporteur)</authority><authority type="jury">Monique Grandbastien (membre invité)</authority><authority type="jury">Christian Retoré (membre invité)</authority></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="fr">French</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Natural Language Processing</term><term xml:lang="en">Rewriting</term><term xml:lang="en">Meaning</term><term xml:lang="fr">Linguistique</term><term xml:lang="fr">Informatique</term><term xml:lang="fr">Langage naturel</term><term xml:lang="fr">Traitement du (informatique)</term><term xml:lang="fr">Réécriture</term><term xml:lang="fr">Système de</term><term xml:lang="fr">Représentation (Linguistique)</term><term xml:lang="fr">Raisonnement</term></keywords><classCode scheme="halDomain" n="info.info-oh">Computer Science [cs]/Other [cs.OH]</classCode><classCode scheme="halTypology" n="THESE">Theses</classCode></textClass><abstract xml:lang="en">This thesis presents several contributions on the theme of recognising textual entailment (RTE). The RTE is the human capacity, given two texts, to determine whether the meaning of the second text could be deduced from the meaning of the first or not. One of the contributions made to the field is a hybrid system of RTE taking analysis of an existing stochastic parser to label them with semantics roles, then turning obtained structures in logical formulas using rewrite rules to finally test the entailment using proof tools. Another contribution of this thesis is the generation of finely annotated tests suites with a uniform distribution of phenomena coupled with a new methodology of systems evaluation using error minning techniques developed by the community of parsing allowing better identification of systems limitations. For this, we create a set of formulas, then we generate annotated syntactics realisations corresponding by using an existing generation system. Then, we test whether or not there is an entailment between each pair of possible syntactics realisations. Finally, we select a subset of this set of problems of a given size and a satisfactory a certain number of constraints using an algorithm that we developed.</abstract><abstract xml:lang="fr">Cette thèse propose plusieurs contributions sur le thème de la détection d'implications textuelles (DIT). La DIT est la capacité humaine, étant donné deux textes, à pouvoir dire si le sens du second texte peut être déduit à partir de celui du premier. Une des contributions apportée au domaine est un système de DIT hybride prenant les analyses d'un analyseur syntaxique stochastique existant afin de les étiqueter avec des rôles sémantiques, puis transformant les structures obtenues en formules logiques grâce à des règles de réécriture pour tester finalement l'implication à l'aide d'outils de preuve. L'autre contribution de cette thèse est la génération de suites de tests finement annotés avec une distribution uniforme des phénomènes couplée avec une nouvelle méthode d'évaluation des systèmes utilisant les techniques de fouille d'erreurs développées par la communauté de l'analyse syntaxique permettant une meilleure identification des limites des systèmes. Pour cela nous créons un ensemble de formules sémantiques puis nous générons les réalisations syntaxiques annotées correspondantes à l'aide d'un système de génération existant. Nous testons ensuite s'il y a implication ou non entre chaque couple de réalisations syntaxiques possible. Enfin nous sélectionnons un sous-ensemble de cet ensemble de problèmes d'une taille donnée et satisfaisant un certain nombre de contraintes à l'aide d'un algorithme que nous avons développé.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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