Paper: Hybrid Learning of Dependency Structures from Heterogeneous Linguistic Resources

ACL ID W08-2126
Title Hybrid Learning of Dependency Structures from Heterogeneous Linguistic Resources
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2008
Authors

In this paper we present our syntactic and semantic dependency parsing system par- ticipated in both closed and open compe- titions of the CoNLL 2008 Shared Task. By combining the outcome of two state-of- the-art syntactic dependency parsers, we achieved high accuracy in syntactic de- pendencies (87.32%). With MRSes from grammar-based HPSG parsers, we achieved significant performance improvement on semantic role labeling (from 71.31% to 71.89%), especially in the out-domain evaluation (from 60.16% to 62.11%).