Probabilistic Graph-based Dependency Parsing with Convolutional Neural Network

Zhisong Zhang, Hai Zhao, Lianhui Qin
2016 Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
This paper presents neural probabilistic parsing models which explore up to thirdorder graph-based parsing with maximum likelihood training criteria. Two neural network extensions are exploited for performance improvement. Firstly, a convolutional layer that absorbs the influences of all words in a sentence is used so that sentence-level information can be effectively captured. Secondly, a linear layer is added to integrate different order neural models and trained with perceptron method. The
more » ... oposed parsers are evaluated on English and Chinese Penn Treebanks and obtain competitive accuracies.
doi:10.18653/v1/p16-1131 dblp:conf/acl/ZhangZQ16 fatcat:zvv2likasrc4xoqif35pu6zwwe