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A WordNet-based semantic approach to textual entailment and cross-lingual textual entailment

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Abstract

In this paper we explain how to build a recognizing textual entailment (RTE) system which only uses semantic similarity measures based on WordNet. We show how the widely used WordNet-based semantic measures can be generalized to build sentence level semantic metrics in order to be used in both mono-lingual and cross-lingual textual entailment. We experiment with a wide variety of RTE datasets and evaluate the contribution of an algorithm which expands the RTE monolingual corpus. Results achieved with this method yielded significant statistical differences when predicting RTE test sets. We provide an efficiency analysis of these metrics drawing some conclusions about their practical utility in recognizing textual entailment. We also analyze the cross-lingual textual entailment task, we create a bilingual English–Spanish corpus, and propose a procedure to create a cross-lingual textual entailment corpus for any pair of languages. Finally, we show that the proposed method is enough to build an average score RTE system in both monolingual and cross-lingual textual entailment, that uses semantic information from WordNet as the only source of lexical-semantic knowledge.

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Notes

  1. http://www.nist.gov/tac/2008/rte/

  2. http://www.investigacion.frc.utn.edu.ar/mslabs/~jcastillo/Sagan-test-suite/

  3. http://www.cogs.susx.ac.uk/users/drh21/

  4. http://marimba.d.umn.edu/cgi-bin/similarity/similarity.cgi

  5. Intel Core 2 Duo 2.00 GHz, 4 GB RAM.

  6. http://www.clef-campaign.org/

  7. http://trec.nist.gov/

  8. http://research.nii.ac.jp/ntcir/index-en.html

  9. http://www.investigacion.frc.utn.edu.ar/mslabs/~jcastillo/Sagan-test-suite/

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  1. National University of Cordoba-FaMAF, Cordoba, Argentina

    Julio Javier Castillo

  2. National Technological University-FRC, Cordoba, Argentina

    Julio Javier Castillo

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  1. Julio Javier Castillo
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Correspondence to Julio Javier Castillo.

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Castillo, J.J. A WordNet-based semantic approach to textual entailment and cross-lingual textual entailment. Int. J. Mach. Learn. & Cyber. 2, 177–189 (2011). https://doi.org/10.1007/s13042-011-0026-z

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