Skip to main content

A Syntactic Textual Entailment System Based on Dependency Parser

  • Conference paper
Computational Linguistics and Intelligent Text Processing (CICLing 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6008))

Abstract

The development of a syntactic textual entailment system that compares the dependency relations in both the text and the hypothesis has been reported. The Stanford Dependency Parser has been run on the 2-way RTE-3 development set and the dependency relations obtained for a text and hypothesis pair has been compared. Some of the important comparisons are: subject-subject comparison, subject-verb comparison, object-verb comparison and cross subject-verb comparison. Corresponding verbs are further compared using the WordNet. Each of the matches is assigned some weight learnt from the development corpus. A threshold has been set on the fraction of matching hypothesis relations based on the development set. The threshold score has been applied on the RTE-4 gold standard test set using the same methods of dependency parsing followed by comparisons. Evaluation scores obtained on the test set show 54.75% precision and 53% recall for YES decisions and 54.45% precision and 56.2% recall for NO decisions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dagan, I., Glickman, O., Magnini, B.: The PASCAL Recognising Textual Entailment Challenge. In: Proceedings of the First PASCAL Recognizing Textual Entailment Workshop (2005)

    Google Scholar 

  2. Bar-Haim, R., Dagan, I., Dolan, B., Ferro, L., Giampiccolo, D., Magnini, B., Szpektor, I.: The Second PASCAL Recognising Textual Entailment Challenge. In: Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, Venice, Italy (2006)

    Google Scholar 

  3. Voorhees, E.M., Harman, D.: Overview of the seventh text retrieval conference. In: Proceedings of the Seventh Text REtrieval Conference (TREC-7). NIST Special Publication (1999)

    Google Scholar 

  4. Giampiccolo, D., Dang, H.T., Magnini, B., Dagan, I., Cabrio, E.: The Fourth PASCAL Recognizing Textual Entailment Challenge. In: TAC 2008 Proceedings (2008), http://www.nist.gov/tac/publications/2008/papers.html

  5. Vanderwende, L., Coughlin, D., Dolan, B.: What syntax can contribute in entailment task. In: Proceedings of the First PASCAL Recognizing Textual Entailment Workshop, pp. 13–16 (2005)

    Google Scholar 

  6. Herrera, J., Peñas, A., Verdejo, F.: Textual Entailment Recognition Based on Dependency Analysis and WordNet. In: Proceedings of the First PASCAL Recognizing Textual Entailment Workshop, pp. 21–24 (2005)

    Google Scholar 

  7. Kouylekov, M., Magnini, B.: Tree Edit Distance for Recognizing Textual Entailment: Estimating the Cost of Insertion. In: Proc. of the PASCAL RTE-2 Challenge, pp. 68–73 (2006)

    Google Scholar 

  8. Blake, C.: The Role of Sentence Structure in Recognizing Textual Entailment. In: Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 101–106 (2007)

    Google Scholar 

  9. Wang, R., Neumann, G.: Recognizing Textual Entailment Using Sentence Similarity based on Dependency Tree Skeletons. In: Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 36–41 (2007)

    Google Scholar 

  10. Varma, V., Krishna, S., Garapati, H., Reddy, K., Pingali, P., Ganesh, S., Gopisetty, H., Bysani, P., Katragadda, R., Sarvabhotla, K., Reddy, V.B., Bharadwaj, R.: Recognizing Textual Entailment (RTE) Track. In: Text analysis conference 2008 Proceedings (2008)

    Google Scholar 

  11. Klein, D., Manning, C.D.: Accurate unlexicalized parsing. In: ACL 2003, pp. 423–430 (2003)

    Google Scholar 

  12. Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)

    MATH  Google Scholar 

  13. RiWordnet API Tool, http://www.rednoise.org/rita/wordnet/documentation/index.htm

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pakray, P., Gelbukh, A., Bandyopadhyay, S. (2010). A Syntactic Textual Entailment System Based on Dependency Parser. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2010. Lecture Notes in Computer Science, vol 6008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12116-6_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-12116-6_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12115-9

  • Online ISBN: 978-3-642-12116-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics