Research on Language and Computation

, Volume 7, Issue 2, pp 209–229

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

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

DOI: 10.1007/s11168-009-9065-y

Cite this article as:
Rus, V., McCarthy, P.M., Graesser, A.C. et al. Res on Lang and Comput (2009) 7: 209. doi:10.1007/s11168-009-9065-y

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.

Keywords

Entailment Paraphrasing Dependencies Intelligent tutoring systems 

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Vasile Rus
    • 1
  • Philip M. McCarthy
    • 2
  • Arthur C. Graesser
    • 3
  • Danielle S. McNamara
    • 3
  1. 1.Department of Computer ScienceThe University of MemphisMemphisUSA
  2. 2.Department of EnglishThe University of MemphisMemphisUSA
  3. 3.Department of PsychologyThe University of MemphisMemphisUSA