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Ontology, Sublanguage, and Semantic Networks in Natural Language Processing

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Advances in Artificial Intelligence

Abstract

The main claim of the paper is that no significant progress in NLP semantics is possible without a comprehensive formal theory. It is demonstrated that, while having a great deal to offer to NLP semantics, linguistic semantics lacks such a theory. It is also argued that model-theoretical semantics, which is based on a formal theory, fails to reach any significant goals with regard to natural language semantics. It does, however, put forward the important idea of anchoring natural meaning representations in the real world. Such a direct anchoring, without the burden and constraints of truth values, is achieved by the ontologically-, sublanguage-, and semantic-network-based approach to NLPS, an approach in which theoretical needs and practical feasibility merge.

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Author information

Authors and Affiliations

  1. Natural Language Processing Laboratory, Purdue University, West Lafayette, Indiana, 47907, USA

    Victor Raskin

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  1. Victor Raskin
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Editors and Affiliations

  1. IBM T.J. Watson Research Center, 10598, Yorktown Heights, NY, USA

    Martin Charles Golumbic

  2. IBM Israel Scientific Center, Technion City, Haifa, Israel

    Martin Charles Golumbic

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© 1990 Springer-Verlag New York, Inc.

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Raskin, V. (1990). Ontology, Sublanguage, and Semantic Networks in Natural Language Processing. In: Golumbic, M.C. (eds) Advances in Artificial Intelligence. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-9052-7_6

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  • DOI: https://doi.org/10.1007/978-1-4613-9052-7_6

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4613-9054-1

  • Online ISBN: 978-1-4613-9052-7

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