Using predicate-argument structures for information extraction

Mihai Surdeanu, Sanda Harabagiu, John Williams, Paul Aarseth

Research output: Contribution to journalConference articlepeer-review

283 Scopus citations


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.

Original languageEnglish (US)
JournalProceedings of the Annual Meeting of the Association for Computational Linguistics
StatePublished - 2003
Externally publishedYes
Event41st Annual Meeting of the Association for Computational Linguistics, ACL 2003 - Sapporo, Japan
Duration: Jul 7 2003Jul 12 2003

ASJC Scopus subject areas

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics


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