Evaluation of a possibilistic classification approach for Arabic texts disambiguation (Evaluation d'une approche de classification possibiliste pour la désambiguïsation des textes arabes) [in French]

Morphological disambiguation of Arabic words consists in identifying their appropriate morphological analysis. In this paper, we present three models of morphological disambiguation of non-vocalized Arabic texts based on possibilistic classification. This approach deals with imprecise training and testing datasets, as we learn from untagged texts. We experiment our approach on two corpora i.e. the Hadith corpus and the Arabic Treebank. These corpora contain data of different types: traditional and modern. We compare our models to probabilistic and statistical classifiers. To do this, we transform the structure of the training and the test sets to deal with imprecise data. Mots-clés : Traitement Automatique des Langues Naturelles, Désambiguïsation Morphologique de l’Arabe, Théorie des Possibilités, Classification Possibiliste.