Inducing Frame Semantic Verb Classes from WordNet and LDOCE

This paper presents SemFrame, a system that induces frame semantic verb classes from WordNet and LDOCE. Semantic frames are thought to have significant potential in resolving the paraphrase problem challenging many languagebased applications. When compared to the handcrafted FrameNet, SemFrame achieves its best recall-precision balance with 83.2% recall (based on SemFrame's coverage of FrameNet frames) and 73.8% precision (based on SemFrame verbs' semantic relatedness to frame-evoking verbs). The next best performing semantic verb classes achieve 56.9% recall and 55.0% precision.

• Type: Conference
• Year: 2004
• Where: ACL
• Authors: Rebecca Green, Bonnie J. Dorr, Philip Resnik
• Keywords: ACL 2004, ACL 2007, Frame Semantic Verb, Semantic Frames, Semantic Verb Classes