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Meaning Representation: From Continuity to Discreteness

This paper presents a geometric approach to meaning representation within the framework of continuous mathematics. Meaning representation is a central issue in Natural Language Processing, in particular for tasks like word sense disambiguation or information extraction. We want here to discuss the relevance of using continuous models in semantics. We don’t want to argue the continuous or discrete nature of lexical meaning. We use continuity as a tool to access and manipulate lexical meaning. Following Victorri (1994), we assume that continuity or discreteness are not properties of phenomena but characterizations of theories upon phenomena. We briefly describe our theoretical framework, the dynamical construction of meaning (Victorri and Fuchs, 1996), then present the way we automatically build continuous semantic spaces from a graph of synonymy and discuss their relevance and utility. We also think that discreteness and continuity can collaborate. We show here how we can complete our geometric representations with informations from discrete descriptions of meaning.