Clustering Polysemic Subcategorization Frame Distributions Semantically

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

• Type: Conference
• Year: 2003
• Where: ACL
• Authors: Anna Korhonen, Yuval Krymolowski, Zvika Marx
• Keywords: ACL 2003, ACL 2007, Nearest Neighbour Methods, Semantic Verb Classes, Undisambiguated Corpus Data