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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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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