Unified Semantic Role Labeling for Verbal and Nominal Predicates in the Chinese Language

Abstract

This article explores unified semantic role labeling (SRL) for both verbal and nominal predicates in the Chinese language. This is done by considering SRL for both verbal and nominal predicates in a unified framework. First, we systematically examine various kinds of features for verbal SRL and nominal SRL, respectively, besides those widely used ones. Then we further improve the performance of nominal SRL with various kinds of verbal evidence, that is, merging the training instances from verbal predicates and integrating various kinds of features derived from SRL for verbal predicates. Finally, we address the issue of automatic predicate recognition, which is essential for nominal SRL. Evaluation on Chinese PropBank and Chinese NomBank shows that our unified approach significantly improves the performance, in particular that of nominal SRL. To the best of our knowledge, this is the first reported work of unified verbal and nominal SRL on Chinese PropBank and NomBank.