Dependency-based Semantic Role Labeling of PropBank

by Richard Johansson , Pierre Nugues

Citations:

9 - 0 self

Datum	Value	Source
TITLE	Dependency-based Semantic Role Labeling of PropBank	SVM HeaderParse 0.2
AUTHOR NAME	Richard Johansson	SVM HeaderParse 0.2
AUTHOR AFFIL	Lund University	SVM HeaderParse 0.2
AUTHOR ADDR	Sweden	SVM HeaderParse 0.2
AUTHOR NAME	Pierre Nugues	SVM HeaderParse 0.2
AUTHOR AFFIL	Lund University	SVM HeaderParse 0.2
AUTHOR ADDR	Sweden	SVM HeaderParse 0.2
ABSTRACT	We present a PropBank semantic role labeling system for English that is integrated with a dependency parser. To tackle the problem of joint syntactic–semantic analysis, the system relies on a syntactic and a semantic subcomponent. The syntactic model is a projective parser using pseudo-projective transformations, and the semantic model uses global inference mechanisms on top of a pipeline of classifiers. The complete syntactic–semantic output is selected from a candidate pool generated by the subsystems. We evaluate the system on the CoNLL-2005 test sets using segment-based and dependency-based metrics. Using the segment-based CoNLL-2005 metric, our system achieves a near state-of-the-art F1 figure of 77.97 on the WSJ+Brown test set, or 78.84 if punctuation is treated consistently. Using a dependency-based metric, the F1 figure of our system is 84.29 on the test set from CoNLL-2008. Our system is the first dependency-based semantic role labeler for PropBank that rivals constituent-based systems in terms of performance. 1	SVM HeaderParse 0.2
CITATIONS	31 found	ParsCit 1.0