Paper: Fast Full Parsing by Linear-Chain Conditional Random Fields

ACL ID E09-1090
Title Fast Full Parsing by Linear-Chain Conditional Random Fields
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

This paper presents a chunking-based dis- criminative approach to full parsing. We convert the task of full parsing into a series of chunking tasks and apply a conditional random field (CRF) model to each level of chunking. The probability of an en- tire parse tree is computed as the product of the probabilities of individual chunk- ing results. The parsing is performed in a bottom-up manner and the best derivation is efficiently obtained by using a depth- first search algorithm. Experimental re- sults demonstrate that this simple parsing framework produces a fast and reasonably accurate parser.