Using machine translation systems to expand a corpus in textual entailment

Abstract

This paper explores how to increase the size of Textual Entailment Corpus by using Machine Translation systems to generate additional t,h pairs. We also analyze the theoretical upper bound of a Corpus expanded by machine translation systems, and propose how it computes the confidence of a classification translator-based RTE system. At the end, we show an algorithm to expand the corpus size using Translator engines and we provide some results over a real RTE system. © 2010 Springer-Verlag Berlin Heidelberg.