Cross-lingual predicate cluster acquisition to improve bilingual event extraction by inductive learning

  • Authors:
  • Heng Ji

  • Affiliations:
  • The City University of New York

  • Venue:
  • UMSLLS '09 Proceedings of the Workshop on Unsupervised and Minimally Supervised Learning of Lexical Semantics
  • Year:
  • 2009

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Abstract

In this paper we present two approaches to automatically extract cross-lingual predicate clusters, based on bilingual parallel corpora and cross-lingual information extraction. We demonstrate how these clusters can be used to improve the NIST Automatic Content Extraction (ACE) event extraction task. We propose a new inductive learning framework to automatically augment background data for low-confidence events and then conduct global inference. Without using any additional data or accessing the baseline algorithms this approach obtained significant improvement over a state-of-the-art bilingual (English and Chinese) event extraction system.