%0 Journal Article
%T Parsing Chinese Based on Lexicalized Model<br>基于词汇化模型的汉语句法分析
%A Cao Hai-long
%A Zhao Tie-jun
%A Li Sheng
%A <br>曹海龙
%A 赵铁军
%A 李生
%J 电子与信息学报
%D 2007
%I 
%X In order to process large-scale real text,a method of building Chinese parser based on lexicalized model is proposed.First,a unified approach for segmentation and part of speech tagging is proposed based on hidden Markov model.The method not only conservers the merits of HMM which is simple and efficient but also improves the tagging accuracy.Then the head-driven model is used to recognize phrases.Head-driven model is a well-known English parsing model;we combine it with segmentation and POS tagging model and thus build a Chinese parser that can operate at the character level.The parser is evaluated on the standard test set.It achieves 77.57% precision and 74.96% recall and outperforms the only previous comparable work significantly.
%K Syntactic parsing
%K Hidden Markov model
%K Head-driven model
%K Syntactic pattern recognition<br>句法分析
%K 隐马尔科夫模型
%K 中心驱动模型
%K 结构模式识别
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=00BDE3CB9A9273E3&yid=A732AF04DDA03BB3&vid=771469D9D58C34FF&iid=9CF7A0430CBB2DFD&sid=F43C60BA2AEFF068&eid=FA7F82B640E17733&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=0&reference_num=10