We introduce a novel type of graphs for NLP – Textual Entailment Graphs (TEG). We present the first gold-standard dataset of TEGs, describe a methodology we developed for their construction and evaluate state-of-the-art RTE engines for this task. We show the utility of TEGs for text exploration and suggest that TEGs might have different usages and that their automatic creation is an interesting...

This paper describes the CLEAR team’s submission to the 2008 Text Analysis Conference under the Recognizing Textual Entailment track. The system breaks text fragments down into fine-grained semantic facets and performs entailment recognition on these. We show that, in the relevant subset of the data, we can achieve 90% accuracy in pinpointing the specific facet of a hypothesis that is not entai...

The Text Analysis Conference (TAC) 2009 competition featured a new textual entailment search task, which extends the 2008 textual entailment task. The goal is to find information in a set of documents that are entailed from a given statement. Rather than designing a system specifically for this task, we investigated the adaptation of an existing artificial believer system to solve this task. Th...

Blogs and forums are widely adopted by online communities to debate about various issues. However, a user that wants to cut in on a debate may experience some difficulties in extracting the current accepted positions, and can be discouraged from interacting through these applications. In our paper, we combine textual entailment with argumentation theory to automatically extract the arguments fr...

In this study, the researcher chose three different vocabulary techniques (Visual Representation, Textual Enhancement, and Glossing) and compared them with traditional method of teaching vocabulary. 80 advanced EFL Learners were assigned as four intact groups (three experimental and one control group) through using a proficiency test and a vocabulary test as a pre-test. In the visual group, stu...

We present two regression models for the prediction of pairwise preference judgments among MT hypotheses. Both models are based on feature sets that are motivated by textual entailment and incorporate lexical similarity as well as local syntactic features and specific semantic phenomena. One model predicts absolute scores; the other one direct pairwise judgments. We find that both models are co...

The Recognizing Textual Entailment System shown here is based on the use of a broad-coverage parser to extract dependency relationships; in addition, WordNet relations are used to recognize entailment at the lexical level. The work investigates whether the mapping of dependency trees from text and hypothesis give better evidence of entailment than the matching of plain text alone. While the use...

While a significant amount of research has been devoted to textual entailment, automated entailment from conversational scripts has received less attention. To address this limitation, this paper investigates the problem of conversation entailment: automated inference of hypotheses from conversation scripts. We examine two levels of semantic representations: a basic representation based on synt...