A Case Study of Copredication over a Deverbal that Reconciles Empirical Data with Computational Semantics

Livy Real 1 Christian Retoré 2
2 TEXTE - Exploration et exploitation de données textuelles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : This paper is about the automated analysis of the lexical and compo-sitional semantics of nominalisation, in particular of felicitous co-predications — infelicitous ones are rejected. We focus on Brazilian Portuguese nominalisation introduced by the suffix-ura but our discussion applies to other nominalisations and languages as well. Much of the theoretical work on deverbals, including ours, concluded that deverbal senses (process, result, location and so on) are rather unforeseeable from the verb and the suffix. The (in)felicity of co-predication, that is the possible conjunction of two predicates which applies to different senses, is also difficult to predict, and in the case of deverbals it is assumed to be (almost) impossible. We present here a study of the CHAVE corpus and show that CHAVE does actually contain some of the supposedly non-existent copredica-tions. We explain our formalisation of sense variation and copredications in our logico-computational framework, Montagovean Generative Lexicon. We analyse the felicitous copredications and explain how the infelicitous ones are rejected. We give possible reasons for the felicity of the observed copredications, and finally we sketch out some guidelines for handling two notions that are necessary to a proper treatment of deverbals, namely local context and degree of semantic felicity.
Type de document :
Communication dans un congrès
Eric McReady. LENLS12: Logic and Engineering of Natural Language Semantics 12, Nov 2015, Tokyo, Japan. ISBN: 978-4-915905-68-1, 2015
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Livy Real, Christian Retoré. A Case Study of Copredication over a Deverbal that Reconciles Empirical Data with Computational Semantics. Eric McReady. LENLS12: Logic and Engineering of Natural Language Semantics 12, Nov 2015, Tokyo, Japan. ISBN: 978-4-915905-68-1, 2015. 〈lirmm-01311129〉

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