Introduction

Recent works in Computational Linguistics show the central role played by the lexicon in language processing, and in particular by the lexical semantics component. Lexicons tend no longer to be a mere enumeration of feature-value pairs but tend to have an intelligent behavior. This is the case, for example, for generative lexicons (Pustejovsky, 1991) which contain, besides feature structures, a number of rules to create new (partial) definitions of word-senses such as rules for conflation and type coercion. As a result, the size of lexical entries describing word-senses has substantially increased. These lexical entries become very hard to be used directly by a natural language parser or generator because their size and complexity allow a priori little flexibility.

Most natural language systems consider a lexical entry as an indivisible whole which is percolated up in the parse/generation tree. Access to features and feature values at grammar rule level is realized by more or less complex procedures (Shieber, 1986; Johnson, 1990; Günthner, 1988). The complexity of real natural language processing systems makes such an approach very inefficient and not necessarily linguistically adequate. In this document, we propose a dynamic treatment of features in grammars, embedded within a Constraint Logic Programming framework (noted as CLP hereafter) which permits us to access a feature-value pair associated to a certain word-sense directly into the lexicon, and only when this feature is explicitly required by the grammar, for example, to make a check. More precisely, this dynamic treatment of features will make use of both constraint propagation techniques embedded within CLP and CLP resolution mechanisms.