Semantic Class Induction and Coreference Resolution

This paper examines whether a learningbased coreference resolver can be improved using semantic class knowledge that is automatically acquired from a version of the Penn Treebank in which the noun phrases are labeled with their semantic classes. Experiments on the ACE test data show that a resolver that employs such induced semantic class knowledge yields a statistically significant improvement of 2% in F-measure over one that exploits heuristically computed semantic class knowledge. In addition, the induced knowledge improves the accuracy of common noun resolution by 2-6%.

• Type: Conference
• Year: 2007
• Where: ACL
• Authors: Vincent Ng
• Keywords: ACL 2007, Computational Linguistics, Learningbased Coreference Resolver, Semantic Class Knowledge, Semantic Classes