Easy-First POS Tagging and Dependency Parsing with Beam Search

Ji Ma, Jingbo Zhu, Tong Xiao, Nan Yang
2013 Annual Meeting of the Association for Computational Linguistics  
In this paper, we combine easy-first dependency parsing and POS tagging algorithms with beam search and structured perceptron. We propose a simple variant of "early-update" to ensure valid update in the training process. The proposed solution 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.
dblp:conf/acl/MaZXY13 fatcat:rpoeg25xtzbbtdvv5jgrqbrkaq