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Annals of Computer Science and Information Systems, Volume 8

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

Word2vec Based System for Recognizing Partial Textual Entailment

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DOI: http://dx.doi.org/10.15439/2016F419

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 513–516 ()

Full text

Abstract. Recognizing textual entailment is typically considered as a binary decision task -- whether a text $T$ entails a hypothesis $H$. Thus, in case of a negative answer, it is not possible to express that $H$ is ``almost entailed'' by $T$. Partial textual entailment provides one possible approach to this issue. This paper presents an attempt to use word2vec model for recognizing partial (faceted) textual entailment. The proposed approach does not rely on language dependent NLP tools and other linguistic resources, therefore it can be easily implemented in different language environments where word2vec models are available.

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