Paper: Faster Parsing by Supertagger Adaptation

ACL ID P10-1036
Title Faster Parsing by Supertagger Adaptation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010

We propose a novel self-training method for a parser which uses a lexicalised gram- mar and supertagger, focusing on increas- ing the speed of the parser rather than its accuracy. The idea is to train the su- pertagger on large amounts of parser out- put, so that the supertagger can learn to supply the supertags that the parser will eventually choose as part of the highest- scoring derivation. Since the supertag- ger supplies fewer supertags overall, the parsing speed is increased. We demon- strate the effectiveness of the method us- ing a CCG supertagger and parser, obtain- ing significant speed increases on newspa- per text with no loss in accuracy. We also show that the method can be used to adapt the CCG parser to new domains, obtain- ing accuracy and speed improvements for Wikipedia a...