Exemplar-Based Sense Modulation

A great deal of psycholinguistic findings reveal that context highlights or obscures certain aspects in the meaning of a word (viz., word sense modulation). Computational models of lexicon, however, are mostly concerned with the ways context selects a meaning for a word (word sense selection). In this paper, we propose a model that combines sense selection with sense modulation. Word senses in this proposal consist of a sense-concept and a sense-view. Furthermore, we outline an exemplar-based approach in which se~se-views are developed gradually and incrementally. A prototype implementation of this model for sentential context is also briefly discussed.