Paper: Using LTAG Based Features In Parse Reranking

ACL ID W03-1012
Title Using LTAG Based Features In Parse Reranking
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2003

We propose the use of Lexicalized Tree Adjoining Grammar (LTAG) as a source of features that are useful for reranking the output of a statistical parser. In this paper, we extend the notion of a tree ker- nel over arbitrary sub-trees of the parse to the derivation trees and derived trees pro- vided by the LTAG formalism, and in ad- dition, we extend the original de nition of the tree kernel, making it more lexi- calized and more compact. We use LTAG based features for the parse reranking task and obtain labeled recall and precision of 89:7%=90:0% on WSJ section 23 of Penn Treebank for sentences of length 100 words. Our results show that the use of LTAG based tree kernel gives rise to a 17% relative difference in f-score im- provement over the use of a linear kernel without LTAG based featu...