acl acl2013 acl2013-297 acl2013-297-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Omer Levy ; Torsten Zesch ; Ido Dagan ; Iryna Gurevych
Abstract: Textual entailment is an asymmetric relation between two text fragments that describes whether one fragment can be inferred from the other. It thus cannot capture the notion that the target fragment is “almost entailed” by the given text. The recently suggested idea of partial textual entailment may remedy this problem. We investigate partial entailment under the faceted entailment model and the possibility of adapting existing textual entailment methods to this setting. Indeed, our results show that these methods are useful for rec- ognizing partial entailment. We also provide a preliminary assessment of how partial entailment may be used for recognizing (complete) textual entailment.
Eneko Agirre, Daniel Cer, Mona Diab, and Aitor Gonzalez-Agirre. 2012. SemEval-2012 Task 6: A pilot on semantic textual similarity. In Proceedings of the 6th International Workshop on Semantic Evaluation, in conjunction with the 1st Joint Conference on Lexical and Computational Semantics, pages 385–393, Montreal, Canada. Luisa Bentivogli, Peter Clark, Ido Dagan, Hoa Dang, and Danilo Giampiccolo. 2011. The seventh pascal recognizing textual entailment challenge. Proceedings of TAC. Peter Clark and Phil Harrison. 2010. Blue-lite: a knowledge-based lexical entailment system for rte6. Proc. of TAC. Ido Dagan, Bill Dolan, Bernardo Magnini, and Dan Roth. 2009. Recognizing textual entailment: Rationale, evaluation and approaches. Natural Language Engineering, 15(4):i–xvii. Myroslava O Dzikovska, Rodney D Nielsen, and Chris Brew. 2012. Towards effective tutorial feedback for explanation questions: A dataset and baselines. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 200–210. Association for Computational Linguistics. Myroslava O. Dzikovska, Rodney Nielsen, Chris Brew, Claudia Leacock, Danilo Giampiccolo, Luisa Bentivogli, Peter Clark, Ido Dagan, and Hoa Trang Dang. 2013. Semeval-2013 task 7: The joint student response analysis and 8th recognizing textual entailment challenge. In *SEM 2013: The First Joint Conference on Lexical and Computational Semantics, Atlanta, Georgia, USA, 13-14 June. Association for Computational Linguistics. Christiane Fellbaum, editor. 1998. WordNet: An Electronic Lexical Database. MIT Press, Cambridge, MA. Rodney D Nielsen, Wayne Ward, and James H Martin. 2009. Recognizing entailment in intelligent tutoring systems. Natural Language Engineering, 15(4):479–501. Philip Resnik. 1995. Using information content to evaluate semantic similarity in a taxonomy. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI 1995), pages 448– 453. Eyal Shnarch, Jacob Goldberger, and Ido Dagan. 2011. A probabilistic modeling framework for lexical entailment. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 558– 563, Portland, Oregon, USA, June. Association for Computational Linguistics. Asher Stern and Ido Dagan. 2011. A confidence model for syntactically-motivated entailment proofs. In Proceedings of the 8th International Conference on Recent Advances in Natural Language Processing (RANLP 2011), pages 455–462. Asher Stern and Ido Dagan. 2012. Biutee: A modular open-source system for recognizing textual entailment. In Proceedings of the ACL 2012 System Demonstrations, pages 73–78, Jeju Island, Korea, July. Association for Computational Linguistics. 455