Paper: Parse Correction with Specialized Models for Difficult Attachment Types

ACL ID D11-1113
Title Parse Correction with Specialized Models for Difficult Attachment Types
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

This paper develops a framework for syntac- tic dependency parse correction. Dependen- cies in an input parse tree are revised by se- lecting, for a given dependent, the best gov- ernor from within a small set of candidates. We use a discriminative linear ranking model to select the best governor from a group of candidates for a dependent, and our model in- cludes a rich feature set that encodes syntac- tic structure in the input parse tree. The parse correction framework is parser-agnostic, and can correct attachments using either a generic model or specialized models tailored to dif- ficult attachment types like coordination and pp-attachment. Our experiments show that parse correction, combining a generic model with specialized models for difficult attach- ment types, can successfully i...