One of the main challenges for computational lexical semantics is to bridge the gap between on the one hand theoretical research on the organization of the lexicon and on the formal representation of word meaning, and on the other hand the increasing request by natural language processing systems of accessing large repositories of lex- ical knowledge. Starting from some recent extensions of Generative Lexicon theory (Pustejovsky 1995, 1998) we present a general model for the development of a set of large-scale lexical resources developed in the context of the SIMPLE project. We will argue that the principles of the Generative Lexicon provide a framework for structuring word meaning which allows for important synergies between research on conceptual structure and the design of formal architectures for the representation of lexical content. The model that we present, which is quite different from standard approaches to semantic classification, is largely motivated by the need to provide appropriate representations for lexical items that cannot be readily handled in existing frameworks.

Building a Semantic Lexicon: Structuring and Generating Concepts

LENCI, ALESSANDRO;
2001-01-01

Abstract

One of the main challenges for computational lexical semantics is to bridge the gap between on the one hand theoretical research on the organization of the lexicon and on the formal representation of word meaning, and on the other hand the increasing request by natural language processing systems of accessing large repositories of lex- ical knowledge. Starting from some recent extensions of Generative Lexicon theory (Pustejovsky 1995, 1998) we present a general model for the development of a set of large-scale lexical resources developed in the context of the SIMPLE project. We will argue that the principles of the Generative Lexicon provide a framework for structuring word meaning which allows for important synergies between research on conceptual structure and the design of formal architectures for the representation of lexical content. The model that we present, which is quite different from standard approaches to semantic classification, is largely motivated by the need to provide appropriate representations for lexical items that cannot be readily handled in existing frameworks.
2001
Busa, F.; Calzolari, N.; Lenci, Alessandro; Pustejovsky, J.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/68666
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