Chinese Question Answering Based on Syntax Analysis and Answer Classification

This paper first conducts rigorous sentence pattern analysis of questions based on the distance between question word and predicate,and then conduct shallow parse of answer candidate sentences.Based on the analysis,we extract question feature set;answer sentence feature set and combined feature set as our features for answer classification.Then we apply maximum entropy model and support vector machine to these features to train answer classifiers.The F-Measures of the two classifiers' experiment conducted on five kinds of fact-based questions achieve 70.87% and 85.75% respectively.