基于依存句法分析的复合事实型问句分解方法

A Decomposition Method for Complex Factoid Questions Based on Dependency Parsing

问答系统一直以来都是自然语言处理领域的研究热点之一,然而现有问答系统技术对复合事实型问句的处理效果并不完美。为了增强问答系统理解复合事实型问句的能力,该文提出了一种针对复合事实型问句的分解方法:使用基于树核的支持向量机对问句的分解类别进行识别,进而使用基于依存句法分析的方法生成分解结果。实验结果显示,在我们所构建的高质量问句分解语料库中,我们的方法对问句分解类别进行了准确的识别,同时也可以较好地生成嵌套型问句的子问句。

Question answering systems have been one of the hot research areas of natural language processing for a long time. To enhance the ability of analyzing complex factoid questions in question answering systems, we presen- ted a novel method to decompose complex factoid questions： using a tree kernel based support vector machine to recognize decomposition categories of questions, and generating decomposition results with a dependency parsing based method. The evaluation shows that based on the high quality question decomposition corpus we had built, our meth- od recognizes question decomposition categories with high performance and generated sub-question series with high quality, especially for the nested-typeones.