2014 | OriginalPaper | Buchkapitel
Improving Multi-pass Transition-Based Dependency Parsing Using Enhanced Shift Actions
verfasst von : Chenxi Zhu, Xipeng Qiu, Xuanjing Huang
Erschienen in: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data
Verlag: Springer International Publishing
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In multi-pass transition-based dependency parsing algorithm, the
shift
actions are usually inconsistent for the same node pair in different passes. Some node pairs have a indeed dependency relation, but the modifier node has not been a complete subtree yet. The bottom-up parsing strategy requires to perform
shift
action for these node pairs. In this paper, we propose a method to improve performance of parsing by using enhanced
shift
actions. These actions can be further used as features for the next parsing decision. Experimental results show that our method is effective to improve the performance of parsing.