Abstract
In artificial intelligence these days, just about anything that’s any good is knowledge-based’. Consequently, knowledge representation formalisms are big business, and are available in a wide range of styles and colors to suit the various demands of consumers in the marketplace. In this paper, I want to argue that consumers in the natural language understanding research community are not as well served as they might be, and many of their needs have been overlooked.
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References
Brachman R.J., Levesque H.J. (1984). The Tractability of Subsumption in Frame-Based Description Languages, in Proc. of the 4th National Conference on AI (AAAI-84), Morgan Kaufmann, Los Altos, CA.
Hayes P.J. (1985). The Second Naive Physics Manifesto, in Brachman R.J., Levesque H.J.(eds.), Readings in Knowledge Representation, Morgan Kaufmann, Los Altos, CA.
Hirst, Graeme (1987). Semantic interpretation and the resolution of ambiguity, Cambridge University Press.
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© 1988 Springer-Verlag Berlin Heidelberg
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Hirst, G. (1988). Knowledge Representation Problems For Natural Language Understanding. In: Trost, H. (eds) 4. Österreichische Artificial-Intelligence-Tagung. Informatik-Fachberichte, vol 176. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-73998-9_1
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DOI: https://doi.org/10.1007/978-3-642-73998-9_1
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