Abstract
The lexical entry for a word must contain all the information needed to construct a semantic representation for sentences that contain the word. Because of that requirement, the formats for lexical representations must be as detailed as the semantic forms. Simple representations, such as features and frames, are adequate for resolving many syntactic ambiguities. However, since those notations cannot represent all of logic, they are incapable of supporting all the function needed for semantics. Richer semantic-based approaches have been developed in both the model-theoretic tradition and the more computational AI tradition. Although superficially in conflict, these two traditions have a great deal in common at a deeper level. Both of them have developed semantic structures that are capable of representing a wide range of linguistic phenomena. The paper compares these approaches, and evaluates their adequacy for various kinds of semantic information that must be stored in the lexicon. It presents conceptual graphs as a synthesis of the logicist and AI representations designed to support the requirements of both.
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