Memory-based resolution of in-sentence scopes of hedge cues

  • Authors:
  • Roser Morante;Vincent Van Asch;Walter Daelemans

  • Affiliations:
  • University of Antwerp, Antwerpen, Belgium;University of Antwerp, Antwerpen, Belgium;University of Antwerp, Antwerpen, Belgium

  • Venue:
  • CoNLL '10: Shared Task Proceedings of the Fourteenth Conference on Computational Natural Language Learning --- Shared Task
  • Year:
  • 2010

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Abstract

In this paper we describe the machine learning systems that we submitted to the CoNLL-2010 Shared Task on Learning to Detect Hedges and Their Scope in Natural Language Text. Task 1 on detecting uncertain information was performed by an SVM-based system to process the Wikipedia data and by a memory-based system to process the biological data. Task 2 on resolving in-sentence scopes of hedge cues, was performed by a memorybased system that relies on information from syntactic dependencies. This system scored the highest F1 (57.32) of Task 2.