Paper: The Benefit Of Stochastic PP Attachment To A Rule-Based Parser

ACL ID P06-2029
Title The Benefit Of Stochastic PP Attachment To A Rule-Based Parser
Venue Annual Meeting of the Association of Computational Linguistics
Session Poster Session
Year 2006
Authors

To study PP attachment disambiguation as a benchmark for empirical methods in nat- ural language processing it has often been reduced to a binary decision problem (be- tween verb or noun attachment) in a par- ticular syntactic configuration. A parser, however, must solve the more general task of deciding between more than two alter- natives in many different contexts. We combine the attachment predictions made by a simple model of lexical attraction with a full-fledged parser of German to de- termine the actual benefit of the subtask to parsing. We show that the combination of data-driven and rule-based components can reduce the number of all parsing errors by 14% and raise the attachment accuracy for dependency parsing of German to an unprecedented 92%.