Automated Semantic Classification of French Verbs

Ingrid Falk 1
1 TALARIS - Natural Language Processing: representation, inference and semantics
Inria Nancy - Grand Est, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : The aim of this work is to explore (semi-)automatic means to create a Levin-type classification of French verbs, suitable for Natural Language Processing. For English, a classification based on Levin's method is VerbNet (Kipper 2005). VerbNet is an extensive digital verb lexicon which systematically extends Levin's classes while ensuring that class members have a common semantics and share a common set of syntactic frames and thematic roles. In this work we reorganise the verbs from three French syntax lexicons, namely Volem, the Grammar-Lexicon (Ladl) and Dicovalence, into VerbNet-like verb classes using the technique of Formal Concept Analysis. We automatically acquire syntactic-semantic verb class and diathesis alternation information. We create large scale verb classes and compare their verb and frame distributions to those of VerbNet. We discuss possible evaluation schemes and finally focus on an evaluation methodology with respect to VerbNet, of which we present the theoretical motivation and analyse the feasibility on a small hand-built example.
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Mémoires d'étudiants -- Hal-inria+
Document and Text Processing. 2008
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Ingrid Falk. Automated Semantic Classification of French Verbs. Document and Text Processing. 2008. 〈hal-01075493〉

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