This paper reports on the performance of a new system for recognizing textual entailment. We present a brief overview of the CERES system and summarize its semantic alignment method for determining entailment. Then, we describe the experiments that were performed, both official and subsequently, against the RTE4 test dataset. We also report on comparison runs against the previous RTE3 developme...

this study was motivated by three factors, which also contribute to its significance for today’s academic writing. first, research articles are the significant means of communication between the writers all over the world. second, persuasion and organization are crucial notions in academic writing where the authors have to consider the academic audiences and their needs.  third, some writers ar...

In this paper we investigate the relation between positive and negative pairs in Textual Entailment (TE), in order to highlight the role of contradiction in TE datasets. We base our analysis on the decomposition of Text-Hypothesis pairs into monothematic pairs, i.e. pairs where only one linguistic phenomenon at a time is responsible for entailment judgment and we argue that such a deeper inspec...

This paper presents a novel approach to Emotion Estimation that assesses the affective content from textual messages. Our main goals are to detect emotion from chat or other dialogue messages and to employ animated agents capable of the emotional reasoning based on the textual interaction. In this paper, the emotion estimation module is applied to a chat system, where avatars associated with ch...

In this paper we describe past and present work dealing with the use of textual resources, out of which semantic information can be extracted in order to provide for semantic annotation and indexing of associated image or video material. Since the emergence of semantic web technologies and resources, entities, relations and events extracted from textual resources by means of Information Extract...

This paper introduces the methods employed by University of Houston team participating in the CL-SciSumm 2017 Shared Task at BIRNDL 2017 to identify reference spans in a reference document given sentences from citing papers. The following approaches were investigated: structural correspondence learning, positional language models, and textual entailment. In addition, we refined our methods from...

We propose new parse-free event-based features to be used in conjunction with lexical, syntactic, and semantic features of texts and hypotheses for Machine Learning-based Recognizing Textual Entailment. Our new similarity features are extracted without using shallow semantic parsers, but still lexical and compositional semantics are not left out. Our experimental results demonstrate that these ...

This paper presents the first round of the task on Cross-lingual Textual Entailment for Content Synchronization, organized within SemEval-2012. The task was designed to promote research on semantic inference over texts written in different languages, targeting at the same time a real application scenario. Participants were presented with datasets for different language pairs, where multi-direct...