Étude d'un modèle d'inférence de connaissances à partir de textes

This article introduces an automated knowledge inference approach taking advantage of relationships extracted from texts. It is based on a novel framework making possible to exploit (i) a generated partial ordering of studied objects (e.g. noun phrases), and (ii) prior knowledge defined into ontologies. This framework is particularly suited for defining information propagation rules based on evidence theory in order to infer new knowledge. The proposed approach is illustrated and evaluated through the definition of a system performing question answering by analyzing texts available on the Web. This case study shows the benefits of structuring processed information (e.g. using prior knowledge) for inferring new knowledge. MOTS-CLÉS : Inférence de connaissances, extraction d’information, modèle de propagation, ontologies, traitement automatique de la langue.