【摘要】 利用外部资源是提升句法分析性能的一种有效方法。本文利用中文词法分析器这一外部资源,提出了一种通用转换方法将中文词法分析器与句法分析器有机地融合在一起。通过基于转换的错误驱动学习和条件随机场解决不同切词、词性标注标准间的转换问题。在句法分析方面,本文提出了多子模型句法分析器,将中心词驱动模型和结构上下文模型有效结合在一起。融合后的中文句法分析性能在宾州中文树库1.0版①测试集上F1值达到了82.5%的最好水平。更多还原

【Abstract】 External resources can be used effectively to improve the parsing accuracy.In this paper,we introduce an external Chinese lexical analysis system to parsing and propose a general transformation methd to integrate them.The Transformation-based Error-driven Learning and Conditional Random Fields are used to solve the problem of transformation between two different standards of segmentation and POS tagging.We also propose a parsing model which combines the Head-driven parsing model and Structural Context parsing model effectively.Experimental results show that our new integrated parsing model achieves an F1 score of 82.5% on the Penn Chinese Tree-Bank Version 1.0,higher than the state-of-art parsers.更多还原