Paper: The Choice of Features for Classification of Verbs in Biomedical Texts

ACL ID C08-1057
Title The Choice of Features for Classification of Verbs in Biomedical Texts
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

We conduct large-scale experiments to in- vestigate optimal features for classification of verbs in biomedical texts. We intro- duce a range of feature sets and associated extraction techniques, and evaluate them thoroughly using a robust method new to the task: cost-based framework for pair- wise clustering. Our best results compare favourably with earlier ones. Interestingly, they are obtained with sophisticated fea- ture sets which include lexical and seman- tic information about selectional prefer- ences of verbs. The latter are acquired au- tomatically from corpus data using a fully unsupervised method.