ZSWSL Text Entailment Recognizing System at NTCIR-9 RITE Task

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.

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