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Exploiting Multilingual Grammars and Machine Learning Techniques to Build an Event Extraction System for Portuguese

  • Vanni Zavarella
  • Hristo Tanev
  • Jens Linge
  • Jakub Piskorski
  • Martin Atkinson
  • Ralf Steinberger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6001)

Abstract

We describe a methodology for building event extraction systems. The approach is based on multilingual domain-specific grammars and exploits weakly supervised machine learning algorithms for lexical acquisition. We report on the process of adapting an already existing event extraction system for the domain of conflicts and crises to the Portuguese language.

Keywords

Semantic Category News Article Learning Stage Lexical Resource Term Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Piskorski, J.: ExPRESS - Extraction Pattern Recognition Engine and Specification Suite. In: Proceedings of the International Workshop Finite-State Methods and Natural language Processing (FSMNLP 2007), Potsdam, Germany (2007)Google Scholar
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    Eleuterio, S., Ranchhod, E., Freire, H., Baptista, J.: A System of Electronic Dictionaries of Portuguese Lingvisticae Investigationes, vol. XIX, p. 2. Jonh Benjamins, Amsterdam (1995)Google Scholar
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    Piskorski, J., Tanev, H., Wennerberg, P.O.: Wennerberg: Extracting Violent Events From On-Line News for Ontology Population. In: 10th International Conference on Business Information Systems (2007)Google Scholar
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    Tanev, H., Magnini, B.: Weakly Supervised Approaches for Ontology Population. In: Proceedings of the European Chapter of the Association of Computational Linguistics (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Vanni Zavarella
    • 1
  • Hristo Tanev
    • 1
  • Jens Linge
    • 1
  • Jakub Piskorski
    • 2
  • Martin Atkinson
    • 1
  • Ralf Steinberger
    • 1
  1. 1.JRC - European Commission 
  2. 2.Polish Academy of Sciences 

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