Paper: Learning the Scope of Hedge Cues in Biomedical Texts

ACL ID W09-1304
Title Learning the Scope of Hedge Cues in Biomedical Texts
Venue Workshop on Biomedical Natural Language Processing
Session
Year 2009
Authors

Identifying hedged information in biomedical literature is an important subtask in informa- tion extraction because it would be mislead- ing to extract speculative information as fac- tual information. In this paper we present a machine learning system that finds the scope of hedge cues in biomedical texts. The sys- tem 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 ro- bustness of the approach, the system is tested on the three subcorpora of the BioScope cor- pus that represent different text types.