Abstract
A predicate is usually omitted from text when it is highly predictable from the context. This omission is due to the effort optimization that humans perform during the language generation process. Authors omit the information that they know the addressee is able to recover effortlessly. Most noun-noun structures including genitives and compounds are result of this process. The goal of this work is to generate automatically and without supervision the paraphrases that make explicit the omitted predicate in these noun-noun structures. The method is general enough to address also the cases were components are Named Entities. The resulting paraphrasing axioms are necessary for recovering the semantics of a text, and therefore, useful for applications such as Question Answering.
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References
Pustejovsky, J.: The Generative Lexicon. Computational Linguistics 17(4) (1991)
Lapata, M., Lascarides, A.: A probabilistic account of logical metonymy. Computational Linguistics 29(2) (2003)
Van Durme, B., Schubert, L.: Open Knowledge Extraction through Compositional Language Processing. In: Symposium on Semantics in Systems for Text Processing (2008)
Clark, P., Harrison, P.: Large-scale extraction and use of knowledge from text. In: The Fifth International Conference on Knowledge Capture, K-CAP 2009 (2009)
Peñas, A., Hovy, E.: Semantic Enrichment of Text with Background Knowledge. In: 1st International FAM-LbRWorkshop, NAACL 2010 (2010)
Levi, J.N.: The Syntax and Semantics of Complex Nominals. Academic Press (1978)
Downing, P.: On the creation and use of English compound nouns. Language 53(4) (1977)
Finin, T.: The Semantic Interpretation of Compound Nominals. Ph.D. thesis, University of Illinois at Urbana Champaign (1980)
Lauer, M.: Corpus statistics meet the compound noun. In: Proceedings of the 33rd Meeting of the Association for Computational Linguistics (1995)
McDonald, D.B.: Understanding Noun Compounds. Tech. rep., CMU TechnicalReport CS-82-102 (1982)
Alshawi, H.: Memory and Context for Language Interpretation. Cambridge University Press, Cambridge (1987)
Fan, J., Barker, K., Porter, B.W.: The knowledge required to interpret noun compounds. In: 18th International Joint Conference on Artificial Intelligence (2003)
Warren, B.: Semantic Patterns of Noun-Noun Compounds. Acta Universitatis Gothoburgensis, Goteborg (1978)
Barker, K., Szpakowicz, S.: Semi-automatic recognition of noun modifier relationships. In: Proceedings of the 36th Annual Meeting of the ACL (1998)
Girju, R., Moldovan, D., Tatu, M., Antohe, D.: On the semantics of noun compounds. Computer Speech and Language 19(4) (2005)
Tratz, S., Hovy, E.: Taxonomy, Dataset, and Classifier for Automatic Noun Compound Interpretation. In: Proceedings of the 48th Annual Meeting of the ACL (2010)
Hendrickx, I., et al.: SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals. In: Proceedings of SemEval 2010 (2010)
Nakov, P., Hearst, M.A.: Using Verbs to Characterize Noun-Noun Relations. In: Euzenat, J., Domingue, J. (eds.) AIMSA 2006. LNCS (LNAI), vol. 4183, pp. 233–244. Springer, Heidelberg (2006)
Butnariu, C., Kim, S.N., Nakov, P., Seaghdha, D.O., Szpakowicz, S., Veale, T.: Semeval-2 task 9: The interpretation of noun compounds using paraphrasing verbs and prepositions. In: Proceedings of the 5th International Workshop on Semantic Evaluation (2010)
Peñas, A., Hovy, E.: Filling Knowledge Gaps in Text for Machine Reading. In: 23rd International Conference on Computational Linguistics, COLING 2010 (2010)
Klein, D., Manning, C.D.: Accurate Unlexicalized Parsing. In: Proceedings of the 41st Meeting of the Association for Computational Linguistics, pp. 423–430 (2003)
Marneffe, M., Manning, C.D.: The Stanford typed dependencies representation. In: COLING 2008 Workshop on Cross-framework and Cross-domain Parser Evaluation (2008)
Bar-Haim, R., Dagan, I., Dolan, B., Ferro, L., Giampiccolo, D., Magnini, B., Szpektor, I.: The second PASCAL Recognising Textual Entailment challenge. In: Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment (2006)
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Peñas, A., Ovchinnikova, E. (2012). Unsupervised Acquisition of Axioms to Paraphrase Noun Compounds and Genitives. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28604-9_32
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DOI: https://doi.org/10.1007/978-3-642-28604-9_32
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