Abstract: 50 lexical and syntax features were chosen to implement selecting experiments of two-feature combinations. Based on those feature combinations, a Chinese sentential semantic recognition method combining C4.5 (decision tree) and SVM was proposed. The method makes full use of the features of high precision of multiple by C4.5 as well as high precision of single and complex by SVM. The final recognition results are determined by synthetic blend of recognition results from C4.5 and SVM, respectively. The experimental data contains 4 500 sentences chosen from Beijing Forest Studio-Chinese Tag Corpus (BFS-CTC). Through ten-fold cross verification, it is concluded that the accuracy rate of proposed method for recognizing sentential semantic type is 92.1%.