Chinese Textual Entailment Recognition Enhanced with Word Embedd...

Textual entailment has been proposed as a unifying generic framework for modeling language variability and semantic inference in different Natural Language Processing (NLP) tasks. By evaluating on NTCIR-11 RITE3 Simplified Chinese subtask data set, this paper firstly demonstrates and compares the performance of Chinese textual entailment recognition models that combine different lexical, syntactic, and semantic features. Then a word embedding based lexical entailment module is added to enhance c