article

Inferring textual entailment with a probabilistically sound calculus*

Author:

Stefan HarmelingAuthors Info & Claims

Natural Language Engineering, Volume 15, Issue 4

Pages 459 - 477

https://doi.org/10.1017/S1351324909990118

Published: 01 October 2009 Publication History

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.

References

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Adams, R. 2006. Textual entailment through extended lexical overlap. In R. Bar-Haim, I. Dagan, B. Dolan, L. Ferro, D. Giampiccolo, B. Magnini and I. Szpektor (eds.), Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, pp. 128-133.

[2]

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.

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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. 871-876. The AAAI Press, Menlo Park, California, USA.

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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 D. Giampiccolo, B. Magnini, I. Dagan, B. Dolan and P. Pantel (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 131-136.

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Bird, S. 2005. NLTK-Lite: efficient scripting for natural language processing. In Fourth International Conference on Natural Language Processing, pp. 1-8.

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Dagan, I., Glickman, O., and Magnini, B. (eds.) 2005. Proceedings of the PASCAL Challenges Workshop on Recognising Textual Entailment.

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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).

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Fellbaum, C. 1998. WordNet: An Electronic Lexical Database. The MIT Press, Cambridge, MA, USA.

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Giampiccolo, D., Magnini, B., Dagan, I., Dolan, B., and Pantel, P. (eds.) 2007. Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing.

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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. 1050-1055. The AAAI Press, Menlo Park, California, USA, 2005.

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Harmeling, S. 2007. An extensible probabilistic transformation-based approach to the third Recognizing Textual Entailment Challenge. In D. Giampiccolo, B. Magnini, I. Dagan, B. Dolan and P. Pantel (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 137-142.

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Hickl, A., and Bensley, J. 2007. A discourse commitment-based framework for Recognizing Textual Entailment. In D. Giampiccolo, B. Magnini, I. Dagan, B. Dolan and P. Pantel (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 171-176.

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Iftene, A., and Balahur-Dobrescu, A. 2007. Hypothesis transformation and semantic variability rules used in Recognizing Textual Entailment. In D. Giampiccolo, B. Magnini, I. Dagan, B. Dolan and P. Pantel (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 125-130.

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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.

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Kouylekov, M., and Magnini, B. 2005. Recognizing Textual Entailment with tree edit distance algorithms. In I. Dagan, O. Glickman and B. Magnini (eds.), Proceedings of the first PASCAL Challenges Workshop on Recognising Textual Entailment, pp. 17-20.

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Kouylekov, M. and Magnini, B. 2007. Tree edit distance for Recognizing Textual Entailment: estimating the cost of insertion. In R. Bar-Haim, I. Dagan, B. Dolan, L. Ferro, D. Giampiccolo, B. Magnini and I. Szpektor (eds.), Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, pp. 68-73.

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Muggleton, S. 1996. Stochastic logic programs. Advances in Inductive Logic Programming 32: 254-64.

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Schölkopf, B. and Smola, A. J. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. The MIT Press, Cambridge, MA, USA.

Digital Library

[19]

Tatu, M., Iles, B., Slavick, J., Novischi, A., and Moldovan, D. 2006 COGEX at the second recognizing textual entailment challenge. In R. Bar-Haim, I. Dagan, B. Dolan, L. Ferro, D. Giampiccolo, B. Magnini and I. Szpektor (eds.), Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, pp. 104-109.

[20]

Tatu, M., and Moldovan, D. 2007 COGEX at RTE 3. In D. Giampiccolo, B. Magnini, I. Dagan, B. Dolan and P. Pantel (eds.), Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 22-27.

Cited By

Bar-Haim RDagan IBerant J(2018)Knowledge-based textual inference via parse-tree transformationsJournal of Artificial Intelligence Research10.5555/2910557.291055854:1(1-57)Online publication date: 20-Dec-2018
https://dl.acm.org/doi/10.5555/2910557.2910558
Androutsopoulos IMalakasiotis P(2018)A survey of paraphrasing and textual entailment methodsJournal of Artificial Intelligence Research10.5555/1892211.189221538:1(135-187)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.5555/1892211.1892215
Zhang ZYao DPang YLu X(2015)Chinese Textual Entailment Recognition Enhanced with Word EmbeddingChinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data10.1007/978-3-319-25816-4_8(89-100)Online publication date: 13-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-319-25816-4_8
Show More Cited By

Index Terms

Inferring textual entailment with a probabilistically sound calculus*
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Hardware
  1. Power and energy
    1. Power estimation and optimization
      1. Platform power issues

Index terms have been assigned to the content through auto-classification.

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cover image Natural Language Engineering

Natural Language Engineering Volume 15, Issue 4

October 2009

130 pages

ISSN:1351-3249

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Cambridge University Press

United States

Publication History

Published: 01 October 2009

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Cited By

Bar-Haim RDagan IBerant J(2018)Knowledge-based textual inference via parse-tree transformationsJournal of Artificial Intelligence Research10.5555/2910557.291055854:1(1-57)Online publication date: 20-Dec-2018
https://dl.acm.org/doi/10.5555/2910557.2910558
Androutsopoulos IMalakasiotis P(2018)A survey of paraphrasing and textual entailment methodsJournal of Artificial Intelligence Research10.5555/1892211.189221538:1(135-187)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.5555/1892211.1892215
Zhang ZYao DPang YLu X(2015)Chinese Textual Entailment Recognition Enhanced with Word EmbeddingChinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data10.1007/978-3-319-25816-4_8(89-100)Online publication date: 13-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-319-25816-4_8
Stern AStern RDagan IFelner ALi HLin COsborne M(2012)Efficient search for transformation-based inferenceProceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 110.5555/2390524.2390564(283-291)Online publication date: 8-Jul-2012
https://dl.acm.org/doi/10.5555/2390524.2390564
Berant JDagan IGoldberger J(2012)Learning entailment relations by global graph structure optimizationComputational Linguistics10.1162/COLI_a_0008538:1(73-111)Online publication date: 1-Mar-2012
https://dl.acm.org/doi/10.1162/COLI_a_00085
Mirkin SDagan IPadó SHajič J(2010)Assessing the role of discourse references in entailment inferenceProceedings of the 48th Annual Meeting of the Association for Computational Linguistics10.5555/1858681.1858804(1209-1219)Online publication date: 11-Jul-2010
https://dl.acm.org/doi/10.5555/1858681.1858804

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