Paper: Prediction of Maximal Projection for Semantic Role Labeling

ACL ID C08-1105
Title Prediction of Maximal Projection for Semantic Role Labeling
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

In Semantic Role Labeling (SRL), argu- ments are usually limited in a syntax sub- tree. It is reasonable to label arguments lo- cally in such a sub-tree rather than a whole tree. To identify active region of argu- ments, this paper models Maximal Pro- jection (MP), which is a concept in D- structure from the projection principle of the Principle and Parameters theory. This paper makes a new definition of MP in S- structure and proposes two methods to pre- dict it: the anchor group approach and the single anchor approach. The anchor group approach achieves an accuracy of 87.75% and the single anchor approach achieves 83.63%. Experimental results also indicate that the prediction of MP improves seman- tic role labeling.