Paper: Prediction of Thematic Rank for Structured Semantic Role Labeling

ACL ID P09-2064
Title Prediction of Thematic Rank for Structured Semantic Role Labeling
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2009
Authors

In Semantic Role Labeling (SRL), it is rea- sonable to globally assign semantic roles due to strong dependencies among argu- ments. Some relations between arguments significantly characterize the structural in- formation of argument structure. In this paper, we concentrate on thematic hierar- chy that is a rank relation restricting syn- tactic realization of arguments. A log- linear model is proposed to accurately identify thematic rank between two argu- ments. To import structural information, we employ re-ranking technique to incor- porate thematic rank relations into local semantic role classification results. Exper- imental results show that automatic pre- diction of thematic hierarchy can help se- mantic role classification.