Paper: Improving Parsing and PP Attachment Performance with Sense Information

ACL ID P08-1037
Title Improving Parsing and PP Attachment Performance with Sense Information
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

To date, parsers have made limited use of se- mantic information, but there is evidence to suggest that semantic features can enhance parse disambiguation. This paper shows that semantic classes help to obtain significant im- provement in both parsing and PP attachment tasks. We devise a gold-standard sense- and parse tree-annotated dataset based on the in- tersection of the Penn Treebank and SemCor, and experiment with different approaches to both semantic representation and disambigua- tion. For the Bikel parser, we achieved a maximal error reduction rate over the base- line parser of 6.9% and 20.5%, for parsing and PP-attachment respectively, using an unsuper- vised WSD strategy. This demonstrates that word sense information can indeed enhance the performance of syntactic disambiguatio...