融合词义信息的文本蕴涵识别方法

Incorporating Word Sense Information for Recognizing Textual Entailment

文本蕴涵识别是对两个文本之间语义关系的有向推理,而词汇的词义对理解文本的语义以及推理文本之间的语义蕴涵关系有着重要作用。因此,为了有效利用词汇的词义信息推断文本之间的语义蕴涵关系,该文提出一种融合词义信息的文本蕴涵识别方法。该方法首次提出将原始的词汇转化为对应的目标词义,然后利用词汇的词义信息改善文本的语义表示和文本间语义关系的推理。实验表明,该文所提出的方法可以有效改善文本间语义关系的推理,从而提升文本蕴涵识别的准确率。

The task of recognizing textual entailment detects whether a given text passage can be inferred from another passage. During inference process, the sense of each word plays an important role in understanding the meaning of the passages and predicting the relationship of the passage-pair. In this paper, we propose a novel approach to incorporate word sense information into the inference mechanism. We first use a word sense disambiguation system to generate the sense of each content word, and then use the information of word sense to improve the representations of the passages and enhance the capability of predicting the entailment relationship of the passage-pair. Experimental results show that our proposed approach can improve the performance effectively.