PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Learning the scope of hedge cues in biomedical texts
Roser Morante and Walter Daelemans
In: BioNLP 2009, 4-5 June 2009, Boulder, Colorado, USA.

Abstract

Identifying hedged information in biomedical literature is an important subtask in information extraction because it would be misleading to extract speculative information as factual information. In this paper we present a machine learning system that finds the scope of hedge cues in biomedical texts. The system is based on a similar system that finds the scope of negation cues. We show that the same scope finding approach can be applied to both negation and hedging. To investigate the robustness of the approach, the system is tested on the three subcorpora of the BioScope corpus that represent different text types.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:5754
Deposited By:Roser Morante
Deposited On:08 March 2010