Paper: Can Human Verb Associations Help Identify Salient Features For Semantic Verb Classification?

ACL ID W06-2910
Title Can Human Verb Associations Help Identify Salient Features For Semantic Verb Classification?
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2006
Authors

This paper investigates whether human as- sociations to verbs as collected in a web experiment can help us to identify salient verb features for semantic verb classes. Assuming that the associations model as- pects of verb meaning, we apply a clus- tering to the verbs, as based on the as- sociations, and validate the resulting verb classes against standard approaches to se- mantic verb classes, i.e. GermaNet and FrameNet. Then, various clusterings of the same verbs are performed on the basis of standard corpus-based types, and eval- uated against the association-based clus- tering as well as GermaNet and FrameNet classes. We hypothesise that the corpus- based clusterings are better if the instan- tiations of the feature types show more overlap with the verb associations, and that the assoc...