This paper describes a heuristic approach to automatically identifying which senses of a machine- readable dictionary (MRD) headword are semantically related versus those which correspond to fundamentally different senses of the word. The inclusion of this information in a lexical database profoundly alters the nature of sense disambiguation: the appropriate "sense" of a polysemous word may now correspond to some set of related senses. Our technique offers benefits both for on-line semantic processing and for the challenging task of mapping word senses across multiple MRDs in creating a merged lexical database.

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Publisher  Association for Computational Linguistics
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