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Inferring textual entailment with a probabilistically sound calculus*

  • STEFAN HARMELING (a1)
Abstract

We introduce a system for textual entailment that is based on a probabilistic model of entailment. The model is defined using a calculus of transformations on dependency trees, which is characterized by the fact that derivations in that calculus preserve the truth only with a certain probability. The calculus is successfully evaluated on the datasets of the PASCAL Challenge on Recognizing Textual Entailment.

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Adams, R. 2006. Textual entailment through extended lexical overlap. In Bar-Haim, R., Dagan, I., Dolan, B., Ferro, L., Giampiccolo, D., Magnini, B. and Szpektor, I. (eds.), Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, pp. 128–133.
Bar-Haim, R., Dagan, I., Dolan, B., Ferro, L., Giampiccolo, D., Magnini, B., and Szpektor, I. (eds.) 2006. Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment.
Bar-Haim, R., Dagan, I., Greental, I., and Shnarch, E. 2007a. Semantic Inference at the Lexical-Syntactic Level. In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI-07), pp. 871876. The AAAI Press, Menlo Park, California, USA.
Bar-Haim, R., Dagan, I., Greental, I., Szpektor, I., and Friedman, M. 2007b. Semantic inference at the lexical–syntactic level for textual entailment recognition. In Giampiccolo, D., Magnini, B., Dagan, I., Dolan, B. and Pantel, P. (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 131–136.
Bird, S. 2005. NLTK-Lite: efficient scripting for natural language processing. In Fourth International Conference on Natural Language Processing, pp. 1–8.
Dagan, I., Glickman, O., and Magnini, B. (eds.) 2005. Proceedings of the PASCAL Challenges Workshop on Recognising Textual Entailment.
de Marneffe, M.-C., MacCartney, B., and Manning, C. D. 2006. Generating typed dependency parses from phrase structure parses. In International Conference on Language Resources and Evaluation (LREC).
Fellbaum, C. 1998. WordNet: An Electronic Lexical Database. The MIT Press, Cambridge, MA, USA.
Giampiccolo, D., Magnini, B., Dagan, I., Dolan, B., and Pantel, P. (eds.) 2007. Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing.
Glickman, O., Dagan, I., and Koppel, M. 2005. A probabilistic classification approach for lexical textual entailment. In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), pp. 10501055. The AAAI Press, Menlo Park, California, USA, 2005.
Harmeling, S. 2007. An extensible probabilistic transformation-based approach to the third Recognizing Textual Entailment Challenge. In Giampiccolo, D., Magnini, B., Dagan, I., Dolan, B. and Pantel, P. (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 137–142.
Hickl, A., and Bensley, J. 2007. A discourse commitment-based framework for Recognizing Textual Entailment. In Giampiccolo, D., Magnini, B., Dagan, I., Dolan, B. and Pantel, P. (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 171–176.
Iftene, A., and Balahur-Dobrescu, A. 2007. Hypothesis transformation and semantic variability rules used in Recognizing Textual Entailment. In Giampiccolo, D., Magnini, B., Dagan, I., Dolan, B. and Pantel, P. (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 125–130.
Klein, D., and Manning, C. D. 2003. Accurate unlexicalized parsing. In Proceedings of the 41st Meeting of the Association for Computational Linguistics, pp. 423–430.
Kouylekov, M., and Magnini, B. 2005. Recognizing Textual Entailment with tree edit distance algorithms. In Dagan, I., Glickman, O. and Magnini, B. (eds.), Proceedings of the first PASCAL Challenges Workshop on Recognising Textual Entailment, pp. 17–20.
Kouylekov, M. and Magnini, B. 2007. Tree edit distance for Recognizing Textual Entailment: estimating the cost of insertion. In Bar-Haim, R., Dagan, I., Dolan, B., Ferro, L., Giampiccolo, D., Magnini, B. and Szpektor, I. (eds.), Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, pp. 68–73.
Muggleton, S. 1996. Stochastic logic programs. Advances in Inductive Logic Programming 32: 254–64.
Schölkopf, B. and Smola, A. J. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. The MIT Press, Cambridge, MA, USA.
Tatu, M., Iles, B., Slavick, J., Novischi, A., and Moldovan, D. 2006 COGEX at the second recognizing textual entailment challenge. In Bar-Haim, R., Dagan, I., Dolan, B., Ferro, L., Giampiccolo, D., Magnini, B. and Szpektor, I. (eds.), Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, pp. 104–109.
Tatu, M., and Moldovan, D. 2007 COGEX at RTE 3. In Giampiccolo, D., Magnini, B., Dagan, I., Dolan, B. and Pantel, P. (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 22–27.
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Natural Language Engineering
  • ISSN: 1351-3249
  • EISSN: 1469-8110
  • URL: /core/journals/natural-language-engineering
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