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Computer Science @ Rochester
Friday, March 27, 2009
3:30 PM
CSB 703
Ben Van Durme
University of Rochester
Deriving Generalized Knowledge from Corpora using WordNet Abstraction
Existing work in the extraction of commonsense knowledge from text has been primarily restricted to factoids that serve as statements about what may possibly obtain in the world. We present an approach to deriving stronger, more general claims by abstracting over large sets of factoids. Our goal is to coalesce the observed nominals for a given predicate argument into a few predominant types, obtained as WordNet synsets. The results can be construed as generically quantified sentences restricting the semantic type of an argument position of a predicate.

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This is joint work with Phil Michalak and Len Schubert.

This is a practice talk for a presentation at EACL the following week.