Inferring Semantics from Collocation Clusters to Represent Verbs and Nouns

Bowen Hui
bowen@cs.utoronto.ca

Department of Computer Science, University of Toronto
10 King's College Road
Toronto, Ontario, Canada


Abstract:

Current lexical semantic theories provide representations at a coarse
grained level. In this paper, I will provide motivations for a fine
grained representation for verbs and nouns. An initial case study is done
to serve as evidence that a more detailed representation is needed for tasks
that require high accuracy rates, such as machine translation. An automatic
approach to gather fine grained information via corpus extraction is
described. Lastly, issues of lexical representation and cross-lingual
translation are discussed.