Paper: Clustering Polysemic Subcategorization Frame Distributions Semantically

ACL ID P03-1009
Title Clustering Polysemic Subcategorization Frame Distributions Semantically
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2003
Authors

Previous research has demonstrated the utility of clustering in inducing semantic verb classes from undisambiguated cor- pus data. We describe a new approach which involves clustering subcategoriza- tion frame (SCF) distributions using the Information Bottleneck and nearest neigh- bour methods. In contrast to previous work, we particularly focus on cluster- ing polysemic verbs. A novel evaluation scheme is proposed which accounts for the effect of polysemy on the clusters, of- fering us a good insight into the potential and limitations of semantically classifying undisambiguated SCF data.