Identification of Sentence-to-Sentence Relations Using a Textual Entailer

Vasile Rus, Philip M. McCarthy, Arthur C. Graesser, Danielle S. McNamara

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

We show in this article how an approach developed for the task of recognizing textual entailment relations can be extended to identify paraphrase and elaboration relations. Entailment is a unidirectional relation between two sentences in which one sentence logically infers the other. There seems to be a close relation between entailment and two other sentence-to-sentence relations: elaboration and paraphrase. This close relation is discussed to theoretically justify the newly derived approaches. The proposed approaches use lexical, syntactic, and shallow negation handling. The proposed approaches offer significantly better results than several baselines. When compared to other paraphrase and elaboration approaches they produce similar or better results. We report results on several data sets: the Microsoft Research Paraphrase corpus, a benchmark for evaluating approaches to paraphrase identification, and a data set collected from high-school students' interactions with an intelligent tutoring system iSTART, which includes both paraphrase and elaboration utterances.

Original languageEnglish (US)
Pages (from-to)209-229
Number of pages21
JournalResearch on Language and Computation
Volume7
Issue number2
DOIs
StatePublished - Nov 4 2009

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Keywords

  • Dependencies
  • Entailment
  • Intelligent tutoring systems
  • Paraphrasing

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Linguistics and Language

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