Paper: Scaling up Automatic Cross-Lingual Semantic Role Annotation

ACL ID P11-2052
Title Scaling up Automatic Cross-Lingual Semantic Role Annotation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

Broad-coverage semantic annotations for training statistical learners are only available for a handful of languages. Previous ap- proaches to cross-lingual transfer of seman- tic annotations have addressed this problem with encouraging results on a small scale. In this paper, we scale up previous efforts by us- ing an automatic approach to semantic anno- tation that does not rely on a semantic on- tology for the target language. Moreover, we improve the quality of the transferred se- mantic annotations by using a joint syntactic- semantic parser that learns the correlationsbe- tween syntax and semantics of the target lan- guage and smooths out the errors from auto- matic transfer. We reach a labelled F-measure for predicates and arguments of only 4% and 9% points, respectively, lower than ...