Paper: Incremental Parsing With The Perceptron Algorithm

ACL ID P04-1015
Title Incremental Parsing With The Perceptron Algorithm
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2004

This paper describes an incremental parsing approach where parameters are estimated using a variant of the perceptron algorithm. A beam-search algorithm is used during both training and decoding phases of the method. The perceptron approach was implemented with the same feature set as that of an existing generative model (Roark, 2001a), and experimental results show that it gives competitive performance to the generative model on parsing the Penn treebank. We demonstrate that train- ing a perceptron model to combine with the generative model during search provides a 2.1 percent F-measure improvement over the generative model alone, to 88.8 percent.