Sciweavers

ACL
2006

Using Machine-Learning to Assign Function Labels to Parser Output for Spanish

13 years 5 months ago
Using Machine-Learning to Assign Function Labels to Parser Output for Spanish
Data-driven grammatical function tag assignment has been studied for English using the Penn-II Treebank data. In this paper we address the question of whether such methods can be applied successfully to other languages and treebank resources. In addition to tag assignment accuracy and f-scores we also present results of a task-based evaluation. We use three machine-learning methods to assign Cast3LB function tags to sentences parsed with Bikel's parser trained on the Cast3LB treebank. The best performing method, SVM, achieves an f-score of 86.87% on gold-standard trees and 66.67% on parser output - a statistically significant improvement of 6.74% over the baseline. In a task-based evaluation we generate LFG functional-structures from the functiontag-enriched trees. On this task we achive an f-score of 75.67%, a statistically significant 3.4% improvement over the baseline.
Grzegorz Chrupala, Josef van Genabith
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where ACL
Authors Grzegorz Chrupala, Josef van Genabith
Comments (0)