Semantic frame analysis is one of the most commonly used semantic analysis methods in Chinese Spoken Dialogue System research. And the two typical ambiguous structures commonly encountered in semantic analysis are relationambiguity and structural–ambiguity. According to the features of these two ambiguous structures, this paper puts forth the Semantic PCFG model based disambiguation strategy to solve structural-ambiguity and the Expectation Model (EM) based disambiguation strategy to solve relation-ambiguity. Efficient algorithms of the two methods are also provided. The experimental results show that applying these two disambiguation strategies can most greatly improve the performance of the language understanding in base-line system. Especially, Sentence Accuracy is improved from 75.7% to 91.5%, and the three targets of Semantic Unit Understanding Rate--Correction, Recall, and Precision are also improved 10% averagely.