Using predicate-argument structures for information extraction

Authors:
Mihai Surdeanu;Sanda Harabagiu;John Williams;Paul Aarseth
Affiliations:
Language Computer Corp., Richardson, Texas;Language Computer Corp., Richardson, Texas;Language Computer Corp., Richardson, Texas;Language Computer Corp., Richardson, Texas
Venue:
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Year:
2003

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Abstract

In this paper we present a novel, customizable IE paradigm that takes advantage of predicate-argument structures. We also introduce a new way of automatically identifying predicate argument structures, which is central to our IE paradigm. It is based on: (1) an extended set of features; and (2) inductive decision tree learning. The experimental results prove our claim that accurate predicate-argument structures enable high quality IE results.