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

This paper presents the system submit-ted by University of Wolverhampton for SemEval-2014 task 1. We proposed a ma-chine learning approach which is based on features extracted using Typed Depen-dencies, Paraphrasing, Machine Transla-tion evaluation metrics, Quality Estima-tion metrics and Corpus Pattern Analysis. Our system performed satisfactorily and obtained 0.711 Pearson correlation for the semantic relatedness task and 78.52 % ac-curacy for the textual entailment task. 1