Thesis Maxime Lefrançois - June 24th 2014 - "Meaning-Text Theory Lexical Semantic Knowledge Representation: Conceptualization, Representation, and Operationalization of Lexicographic Definitions"

I am pleased to announce the defence of my PhD thesis, “ Meaning-Text Theory Lexical Semantic Knowledge Representation: Conceptualization, Representation, and Operationalization of Lexicographic Definitions ”. 

The defence will take place on Tuesday June 24th, at 2pm in room Euler Violet at Inria Sophia Antipolis. 



Best regards, 

Maxime Lefrançois 

Attaché de l'Enseignement et de la Recherche, IUT Nice côte d'azur 

PhD Student Wimmics Team, Inria/I3S 
http://maxime-lefrancois.info 



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Jury : 

DR. Nathalie Aussenac-Gilles, Université de Toulouse, IRIT, CNRS, Toulouse , reviewer 

Pr. Igor Boguslavsky, Universidad Politécnica de Madrid & Russian Academy of Sciences, Moscow , reviewer 

Pr. Marie-Laure Mugnier, Université Montpellier 2, LIRMM/Inria , reviewer 

Pr. Andrea Tettamanzi, Université de Nice-Sophia Antipolis , examiner 



Advisor : 

DR. Fabien Gandon, Inria Sophia Antipolis-Méditerranée 

Co-Advisor : 

Pr. Christian Boitet, Université Joseph Fourier, LIG, Grenoble 



Abstract: 

We present our research in applying knowledge engineering to linguistics. In particular, to linguistic predicates, linguistic representations, and lexicographic definitions of the Meaning-Text Theory (MTT). We adopt a three-step methodology. 

We first study the MTT conceptualization, and show how it should be extended to ease its formalization. We therefore justify the need of defining a new deep semantic, graph-based, representation level for the Meaning-Text model. We define the notion of deep semantic unit types and its actantial structure: a set of signed obligatory, optional or forbidden actant slots with lexicalized semantic roles as labels. We show that their hierarchical organization may correspond to a hierarchy of meanings, inside which actantial structures are inherited and specialized. We re-conceptualize lexicographic definitions at the deep semantic level, and at the level of dictionaries. Finally, we present a definition editor prototype based on graph direct manipulation, which will allow us, in future work, to integrate our formal model into explanatory combinatorial lexicographic projects. 

We then propose a knowledge representation formalism adapted for this conceptualization. We demonstrate that Description Logics and the Conceptual Graphs formalism do not fit our needs. This leads us to construct a new knowledge representation formalism: the Unit Graphs formalism. 

Finally, we operationalize the Unit Graphs formalism. We assign it a formal semantic model, which we create based on model theory and relational algebra. We then show that the reasoning decidability conditions match the intuitions that lexicographers have. We also provide an implementation using semantic web standards, which enable us to use existing architectures for sharing, interoperability, and knowledge querying over the web of lexical linked data.