Abstract
We present our experiments on Recognizing Textual Entailment based on modeling the entailment relation as a classification problem. As features used to classify the entailment pairs we use a symmetric similarity measure and a non-symmetric similarity measure. Our system achieved an accuracy of 66% on the RTE-3 development dataset (with 10-fold cross validation) and accuracy of 63% on the RTE-3 test dataset.
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References
Castro-Sánchez, N.A., Sidorov, G.: Analysis of Definitions of Verbs in an Explanatory Dictionary for Automatic Extraction of Actants based on Detection of Patterns. In: Hopfe, C.J., Rezgui, Y., Métais, E., Preece, A., Li, H. (eds.) NLDB 2010. LNCS, vol. 6177, pp. 233–239. Springer, Heidelberg (2010)
Corley, C., Mihalcea, R.: Measuring the semantic similarity of texts. In: Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment, Ann Arbor (2005)
Dagan, I., Glickman, O.: Probabilistic textual entailment: Generic applied modeling of language variability. In: PASCAL workshop on Text Understanding and Mining (2004); Monz, C., de Rijke, M.: Light-Weight Entailment Checking for Computational Semantic. In: Blackburn, P., Kohlhase, M. (eds.) Proceedings ICoS-3 (2001)
De Salvo Braz, R., Girju, R., Punyakanok, V., Frentiu, D.M.: An Inference Model for Word Sense Disambiguation. In: Proceedings of KEPT 2007, Knowledge Engineering Principles and Techniques, Workshop on Recognising Textual Entailment, vol. I (2007)
Ferrés, D., Rodrí́guez, H.: Machine Learning with Semantic-Based Dis-tances Between Sentences for Textual Entailment. In: Proceedings of the Third Challenge Workshop Recognising Textual Entailment, Prague, Czech Republic (2007)
Glickman, O., Dagan, I., Koppel, M.: Web Based Probabilistic Textual Entailment. In: Proceedings of the PASCAL Challenges Workshop on Recognising Textual Entailment (2005)
Hobbs, J.R.: Ontological promiscuity. In: Proceedings of the 23rd annual meeting on Association for Computational Linguistics (1985)
Inkpen, D., Kipp, D., Nastase, V.: Machine Learning Experiments for Textual Entailment. In: Proceedings of the Second Challenge Workshop Recognising Textual Entailment, Venice, Italy, April 10, pp. 17–20 (2006)
Kouylekov, M., Magnini, B.: Tree Edit Distance for Recognizing Textual Entailment: Estimating the Cost of Insertion. In: Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, Venice, Italy (2006)
Li, B., Irwin, J., Garcia, E.V., Ram, A.: Machine Learning Based Semantic Inference: Experiments and Observations at RTE-3. In: Proceedings of the Third Challenge Workshop Recognising Textual Entailment, Prague, Czech Republic (2007)
Malakasiotis, P., Androutsopoulos, I.: Learning Textual Entailment using SVMs and String Similarity Measures. In: Proceedings of the Third Challenge Workshop Recognising Textual Entailment, Prague, Czech Republic (2007)
Pérez, D., Alfonseca, E.: Application of the Bleu algorithm for recognising textual entailments. In: Proceedings of the First Challenge Workshop Recognising Textual Etailment, Southampton, U.K (2005)
Ríos, M., Gelbukh, A., Bandyopadhyay, S.: Recognizing Textual Entailment with Statistical Methods. In:MCPR 2010, 2nd Mexican Conference on Pattern Recognition (2010) (to be published)
Tatar, D., Gabriela, S., Andreea-Diana, M., Rada, M.: Textual Entailment as a Directional Relation. Journal of Research and Practice in Information Technology (2009)
Witten, H., Frank, E.: Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann, San Francisco (2005)
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Ríos Gaona, M.A., Gelbukh, A., Bandyopadhyay, S. (2010). Recognizing Textual Entailment Using a Machine Learning Approach. In: Sidorov, G., Hernández Aguirre, A., Reyes García, C.A. (eds) Advances in Soft Computing. MICAI 2010. Lecture Notes in Computer Science(), vol 6438. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16773-7_15
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DOI: https://doi.org/10.1007/978-3-642-16773-7_15
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