🚀 go-pugleaf

           Department of Computer Science, University of Toronto
              (GB = Galbraith Building, 35 St. George Street)

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                                AI SEMINAR
              GB221, at 11:00 a.m., Thursday 15 October 1992

                             James Pustejovsky
             Computer Science Department, Brandeis University

                          "Metonymy as Coercion"

Traditionally, semantic information in computational lexicons is limited to
notions such as selectional restrictions or domain-specific constraints,
encoded in a static representation.  This information is typically used in
NLP by a simple knowledge-manipulation mechanism limited to an ability to
match valences of structurally related words.  This holds for most current
views of metonymy and lexical ambiguity as well.  In this talk I will argue
against such enumerative theories of word senses and describe recent work
in generative lexicon theory that treats varieties of metonymy as cases of
type coercion.

This theory makes use of a knowledge-representation framework offering a
richer, more expressive vocabulary for lexical information.  In particular,
by performing specialized inference over the ways in which aspects of
knowledge structures of words in context can be composed, mutually
compatible and contextully relevant lexical components of words and phrases
are highlighted.  I discuss the relevance of this view of the lexicon, as
an explanatory device accounting for language creativity, as well as a
mechanism underlying the implementation of open-ended natural language
processing systems.  In particular, we demonstrate how lexical ambiguity
resolution---now an integral part of the same procedure that creates the
semantic interpretation of a sentence itself---becomes a process not of
selecting from a pre-determined set of senses, but of highlighting certain
lexical properties brought forth by, and relevant to, the current context.