Paper: A Comparative Study on Generalization of Semantic Roles in FrameNet

ACL ID P09-1003
Title A Comparative Study on Generalization of Semantic Roles in FrameNet
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

A number of studies have presented machine-learning approaches to semantic role labeling with availability of corpora such as FrameNet and PropBank. These corpora define the semantic roles of predi- cates for each frame independently. Thus, it is crucial for the machine-learning ap- proach to generalize semantic roles across different frames, and to increase the size of training instances. This paper ex- plores several criteria for generalizing se- mantic roles in FrameNet: role hierar- chy, human-understandable descriptors of roles, semantic types of filler phrases, and mappings from FrameNet roles to the- matic roles of VerbNet. We also pro- pose feature functions that naturally com- bine and weight these criteria, based on the training data. The experimental result of the role classific...