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 …

We present a rule-based method for recognizing entailment relation between a pair of text
fragments by comparing their dependency tree structures. We used a dependency parser to …

Multi-document discourse parsing aims to automatically identify the relations among textual
spans from different texts on the same topic. Recently, with the growing amount of …

We explore various machine learning-based classifiers applied to rule-based features for
recognizing textual entailment. The features, extracted with a set of synthesized matching …

In this paper I outline part of the results of fifteen years of research of the Natural Language
Processing (NLP) Laboratory of CIC-IPN. NLP is a set of technologies that in long run will …

We propose a method for automatic recognition of textual entailment based on word sense
disambiguation using cosine similarity proposed by Abdalgader and Skabar. This algorithm …

Abstract Recognizing Textual Entailment (RTE) is to predict whether one text fragment can
semantically infer another, which is required across multiple applications of natural …

Given two textual fragments, called a text and a hypothesis, respectively, recognizing textual
entailment (RTE) is a task of automatically deciding whether the meaning of the second …

Measuring semantic similarity is a task needed in many Natural Language Processing (NLP)
applications. For example, in Machine Translation evaluation, semantic similarity is used to …

This work proposes a model for recognition of textual entailment by presenting a new
approach through the combined use of syntactic analysis, morphology, linguistic rules …