Paper: Global Learning of Labeled Dependency Trees

ACL ID D07-1127
Title Global Learning of Labeled Dependency Trees
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007

In the paper we describe a dependency parser that uses exact search and global learning (Crammer et al. , 2006) to produce labelled dependency trees. Our system inte- grates the task of learning tree structure and learning labels in one step, using the same set of features for both tasks. During la- bel prediction, the system automatically se- lects for each feature an appropriate level of smoothing. We report on several exper- iments that we conducted with our system. In the shared task evaluation, it scored better than average.