UZurich in the BioNLP 2009 shared task

  • Authors:
  • Kaarel Kaljurand;Gerold Schneider;Fabio Rinaldi

  • Affiliations:
  • University of Zurich, Switzerland;University of Zurich, Switzerland;University of Zurich, Switzerland

  • Venue:
  • BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
  • Year:
  • 2009

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Abstract

We describe a biological event detection method implemented for the BioNLP 2009 Shared Task 1. The method relies entirely on the chunk and syntactic dependency relations provided by a general NLP pipeline which was not adapted in any way for the purposes of the shared task. The method maps the syntactic relations to event structures while being guided by the probabilities of the syntactic features of events which were automatically learned from the training data. Our method achieved a recall of 26% and a precision of 44% in the official test run, under "strict equality" of events.