CYUT Chinese Textual Entailment Recognition System for NTCIR-10 RITE-2
نویسندگان
چکیده
ABSTRACT Textual Entailment (TE) is a critical issue in natural language processing (NLP). In this paper we report our approach to the Chinese textual entailment and the system result on NTCIR-10 RITE-2 both simplified and traditional Chinese dataset. Our approach is based on more observation on training data and finding more types of linguistic features. The approach is a complement to the traditional machine learning approach, which treat every pair in a standard process. In the official runs, we tested three types of entailment features, i.e. the usage of negative words, time expression, and numbers. The experimental result is promising; we find this extensible approach can include more types.
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