| Abstract | This paper describes the generation of a lexicon for a principle-based parser (Minipar[5,6]) using descriptions of verbs based on Lexical-Conceptual Structure (LCS [1,2]).1
We aim to determine how much syntactic information we can obtain from a semantic-
based lexicon. More specifically, we aim to provide a general approach to projection of
syntactic entries from semantic (language-independent) lexicons-and to test the effect
of such lexicons on parser performance. Verbs are grouped together into classes-each
denoted by an LCS representation adn the thematic grid. These are mapped systemat-
ically into syntactic categories associated with entries in the Minipar parser. The main
advantage of this LCS-to-syntax projection is language protability: We currently have
LCS lexicons for English, Arabic, Spanish, and Chinese; thus, our LCS-projection ap-
proach allows us to produce syntactic lexicons for parsing in each of these languages.
For comparing the performance of the projection from the LCS to Minpar coes, we also
generated the mappings for the codes of Longman's Directionary of Contemporary En-
glish (LDOCE [8])-the most comprehensive online dictionary for syntactic categorization.
Preliminary experiments indicate that our approach yields a categorization of verbs with
58% precision and 65% recall as measured against LDOCE-with an improved precision
of 74% when redundancy is removed. The next section presents a brief description of
each code set we use. In Section 3, we explain how we generated Minipar codes from
LCS representation. Finally, Section 4, discusses our experiments and results.
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