ZSWSL Text Entailment Recognizing System at NTCIR-9 RITE Task

This paper describes our system on simplified Chinese textual entailment recognizing RITE task at NTCIR-9. Both lexical and semantic features are extracted using NLP methods. Three classification models are used and compared for the classification task, Rule-based algorithms, SVM and C4.5. C4.5 gives the best result on testing data set. Evaluation at NTCIR-9 RITE shows 72 % accuracy on BC subtask and 61.9 % accuracy on MC subtask