Paper: Easy-First POS Tagging and Dependency Parsing with Beam Search

ACL ID P13-2020
Title Easy-First POS Tagging and Dependency Parsing with Beam Search
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2013
Authors

In this paper, we combine easy-first de- pendency parsing and POS tagging algo- rithms with beam search and structured perceptron. We propose a simple variant of ?early-update? to ensure valid update in the training process. The proposed so- lution can also be applied to combine beam search and structured perceptron with other systems that exhibit spurious ambiguity. On CTB, we achieve 94.01% tagging accuracy and 86.33% unlabeled attachment score with a relatively small beam width. On PTB, we also achieve state-of-the-art performance.