A Survey of Paraphrasing and Textual Entailment Methods

Dependency-based paraphrasing for recognizing textual entailment

This paper addresses syntax-based paraphrasing methods for Recognizing Textual Entailment (RTE). In particular, we describe a dependency-based paraphrasing algorithm, using the DIRT data set, and its application in the context of a straightforward RTE system based on aligning dependency trees. We find a small positive effect of dependency-based paraphrasing on both the RTE3 development and test...

Paraphrase and Textual Entailment Recognition and Generation

Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods, on the other hand, recognize, generate, or extract pairs of natural language expressions, such that a human who reads (and trusts) the first element of a pair would most likely infer that the other element is also tr...

A C L 2 0 0 7 Proceedings of the ACL - PASCAL Workshop on Textual Entailment and Paraphrasing June 28 - 29 , 2007 Prague , Czech Republic

UoW: NLP techniques developed at the University of Wolverhampton for Semantic Similarity and Textual Entailment

This paper presents the system submitted by University of Wolverhampton for SemEval-2014 task 1. We proposed a machine learning approach which is based on features extracted using Typed Dependencies, Paraphrasing, Machine Translation evaluation metrics, Quality Estimation metrics and Corpus Pattern Analysis. Our system performed satisfactorily and obtained 0.711 Pearson correlation for the sema...

Paraphrase and Textual Entailment Generation

One particular information can be conveyed by many different sentences. This variety concerns the choice of vocabulary and style as well as the level of detail (from laconism or succinctness to total verbosity). Although verbosity in written texts is considered bad style, generated verbosity can help natural language processing (NLP) systems to fill in the implicit knowledge. The paper presents...