Paper: Sparse Bayesian Classification Of Predicate Arguments

ACL ID W05-0624
Title Sparse Bayesian Classification Of Predicate Arguments
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2005
Authors

We present an application of Sparse Bayesian Learning to the task of semantic role labeling, and we demonstrate that this method produces smaller classifiers than the popular Support Vector approach. We describe the classification strategy and the features used by the classifier. In par- ticular, the contribution of six parse tree path features is investigated.