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Homer, the Author of The Iliad and the Computational-Linguistic Turn

Chapter
Part of the Text, Speech and Language Technology book series (TLTB, volume 36)

This paper analyzes two sets of opposing opinions about the nature of meaning representations and knowledge resources. The first of these axes of disagreement is the opposition between an ineffable, “revealed” language of thought in the Fodor tradition and Wilks’ position that (using its strongest formulation) elements of the language of knowledge representation are essentially elements of a natural language. The second opposition is between a “scientifically” defined ontology, in Guarino’s sense, and human-oriented resources of knowledge about language, such as MRDs or WordNet. An attempt will be made to clarify some of the motivation behind these differing opinions. I will try to formulate my own positions on the above issues and will use as illustrations some modules of ontological semantics, a computationally-tractable theory of meaning, as implemented in the OntoSem text analyzer and the knowledge resources that support it

Keywords

Word Sense Knowledge Resource Word Sense Disambiguation World Knowledge Ontological Concept 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Austin, J.L. 1962. How to do Things with Words. Oxford: Clarendon.Google Scholar
  2. Beale, S., S. Nirenburg and M. McShane. 2003. Just-in-time Grammar. In: Proceedings of the 2003 International Multiconference in Computer Science and Computer Engineering. Las Vegas, Nevada.Google Scholar
  3. Bergmann, G. 1964. Logic and Reality. Madison, WI: University of Wisconsin Press.Google Scholar
  4. Brachman, R. and H. Levesque. 2004. Knowledge Representation and Reasoning. San Francisco: Morgan Kaufmann.Google Scholar
  5. Brewster, C., J. Iria, F. Ciravegna and Y. Wilks. (2005) The Ontology: Chimaera or Pegasus, In: Proceedings of the Dagstuhl Seminar on Machine Learning for the Semantic Web.Google Scholar
  6. Briscoe. E. J. and A. Copestake. 1991. Sense Extensions as Lexical Rules. In: Proceedings of the IJCAI Workshop on Computational Approaches to Non-Literal Language. Sydney, Australia.Google Scholar
  7. Caws, Peter. 1967. Scientific Method. In: Paul Edwards (Editor-in-Chief), Encyclopedia of Philosophy. Vol. 7, New York: Macmillan, pp. 339–343.Google Scholar
  8. Chafe, W.L. 1977. Creativity in verbalization and its implications of the nature of stored knowledge. In: R.O. Freedle (Ed.), Discourse Production and Comprehension. Norwood, NJ: Ablex, pp. 41–56.Google Scholar
  9. Fellbaum, C. 1998. Towards a Representation of Idioms in WordNet. In: Proceedings of the COLING-ACL Workshop on the Usage of WordNet in Natural Language Processing Systems. Montreal.Google Scholar
  10. Fellbaum, C. 1999. Verb semantics via conceptual and lexical relations. In E. Viegas (Ed.), Breadth and Depth of the Lexicon. Dordrecht, Holland: Kluwer Academic Publishers, pp. 247–262.Google Scholar
  11. Fikes, R., J. Jenkins and G. Frank. 2003. JTP: A System Architecture and Component Library for Hybrid Reasoning. In: Proceedings of the Seventh World Multiconference on Systemics, Cybernetics, and Informatics. Orlando, Florida, USA.Google Scholar
  12. Fodor, JA. and E. Lepore. 1998. The Emptiness of the Lexicon: Critical Reflections on J. Pustejovsky’s The Generative Lexicon. Linguistic Inquiry, 29: 2.Google Scholar
  13. Gangemi, A., Guarino, N. and A. Oltramari. 2001. Conceptual Analysis of Lexical Taxonomies: The Case of WordNet Top-Level. In: Proceedings of FOIS 2001. Maine.Google Scholar
  14. Guarino, N. 1997. Understanding, building and using ontologies. International Journal of Human-Computer Studies, 46.Google Scholar
  15. Guarino, N. 1998. Formal ontologies and information systems. In: Proceedings of the First International Conference on Formal Ontologies in Information Systems. Trento, June.Google Scholar
  16. Guo, C. 1995. Machine tractable dictionaries: Design and construction. Norwood, NJ: Ablex.Google Scholar
  17. Hacker, P.M.S. 1996. Wittgenstein’s Place in Twentieth Century Analytic Philosophy. Oxford University Press.Google Scholar
  18. Halliday, M.A.K. 1985. An Introduction to Functional Grammar. London-Baltimore: E. Arnold.Google Scholar
  19. Hempelmann, C., V. Raskin, and K. E. Triezenberg. 2006. Computer, Tell Me a Joke ... but Please Make it Funny: Computational Humor with Ontological Semantics. In: Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Melbourne Beach, Florida, USA, May 11–13.AAAI Press, pp. 746–751.Google Scholar
  20. Ide, N. and J. Véronis. 1993. Extracting Knowledge Bases from Machine-Readable Dictionaries: Have We Wasted Our Time? In: Proceedings of the First International Conference on Building and Sharing of Very Large-Scale Knowledge Bases (KB&KS’93). Tokyo, Japan.Google Scholar
  21. Ide, N. and Y. Wilks. forthcoming. Making sense about sense. In E. Agirre and P. Edmonds. (Eds.), Word Sense Disambiguation: Algorithms and Applications. Springer.Google Scholar
  22. Iordanskaja, L., R. Kittredge and A. Polguère. 1991. Lexical selection and paraphrase in a meaning-text generation model. In: C. Paris, W. Swartout and W. Mann. (Eds.), Natural-Language Generation in Artificial Intelligence and Computational Linguistics. Boston: Kluwer Academic Publishers.Google Scholar
  23. Java, A., T. Finin and S. Nirenburg. 2005. Integrating Language Understanding Agents into the Semantic Web. In: Proceedings of the First International Symposium on Agents and the Semantic Web. Arlington. VA, November.Google Scholar
  24. Java, A., T. Finin and S. Nirenburg. 2006. Text Understanding Agents and the Semantic Web. In: Proceedings of the 39th Hawaii International Conference on System Sciences.Google Scholar
  25. Johnston, R. 2004. Ice cream verbals. The Journal of the Law Society of Scotland, June.Google Scholar
  26. Kahneman, D., P. Slovik and A. Tversky (Eds.) 1982. Judgment Under Uncertainty: Heuristics and Biases. Cambridge: Cambridge University Press.Google Scholar
  27. Kapur, N. (ed.) 1997. Injured Brains fo Medical Minds: Views from Within. Oxford University Press.Google Scholar
  28. Katz, J. J. and J.A.Fodor. 1963. The structure of a semantic theory. Language, 39:1.CrossRefGoogle Scholar
  29. Kripke, S.A. 1982. Naming and Necessity. Harvard.Google Scholar
  30. Landauer, T.K., P.W. Foltz and D. Laham. 1998. Introduction to latent semantic analysis. Discourse Processes, 25.Google Scholar
  31. Mahesh, K., S. Nirenburg and S. Beale. 1997. If You Have It, Flaunt It: Using Full Ontological Knowledge for Word Sense Disambiguation. In: Proceedings of Theoretical and Methodological Issues in Machine Translation (TMI-97). Santa Fe, NM.Google Scholar
  32. Mann, W.C. and C. Matthiessen. 1983. NIGEL: A Systemic Grammar for Text Generation. Technical Report ISI/RR-85–105, Information Sciences Institute, Marina del Rey, California.Google Scholar
  33. McCawley, J. 1981. Everything that Linguists have Always Wanted to know About Logic (but were ashamed to ask). Chicago: University of Chicago Press, and Oxford: Blackwell.Google Scholar
  34. McDermott, D. 1978. Tarskian semantics, or No notation without denotation. Cognitive Science, 2:3.Google Scholar
  35. McShane, M. 2005. A Theory of Ellipsis. Oxford University Press.Google Scholar
  36. McShane, M., S. Beale and S. Nirenburg. 2004. OntoSem Methods for Processing Semantic Ellipsis. In: Proceedings of the Workshop on Computational Lexical Semantics at HLT-NAACL 2004. Boston, May.Google Scholar
  37. McShane, M., S. Nirenburg, S. Beale and T. O’Hara. 2005. Semantically Rich Human-aided Machine Annotation. In: Proceedings the Workshop on Frontiers in Corpus Annotation II: Pie in the Sky, ACL-05, Ann Arbor, MI.Google Scholar
  38. Mel’ˇuk, I. 1995. The Russian Language in the Meaning-Text Perspective. Vienna/Moscow: Wiener Slawistischer Almanach.Google Scholar
  39. Mel’áuk, I., A. Clas and A. Polguère. 1995. Introduction à la lexicologie explicative et combinatoire. Louvain-la-Neuve: Duculot.Google Scholar
  40. Mihalcea, R. and D. Moldovan. 1998. Word sense disambiguation based on semantic density. In: Proceedings of the COLING-ACL Workshop on the Usage of WordNet in Natural Language Processing Systems. Montreal.Google Scholar
  41. Mitkov, R. 1998. Robust Pronoun Resolution with Limited Knowledge. In: Proceedings of ACL.Google Scholar
  42. Nirenburg, S. and V. Raskin. 2004. Ontological Semantics. Cambridge, MA: MIT Press.Google Scholar
  43. Nirenburg, S. and Wilks, Y. (2001) What’s in a symbol: ontology, representation and language. Journal of Experimental and Theoretical Artificial Intelligence(JETAI), 13(1): 9–23.Google Scholar
  44. Palmer, M., H. Dang and C. Fellbaum. forthcoming. Making fine-grained and coarse-grained sense distinctions, both manually and automatically. Journal of Natural Language Engineering.Google Scholar
  45. Pustejovsky, J. 1995. The Generative Lexicon. Cambridge, MA: MIT Press.Google Scholar
  46. Raskin, V. 1986. Semantic Mechanisms of Humor. Dordrecht: Reidel.Google Scholar
  47. Roy, J.-M. 1998. Cognitive Turn and Linguistic Turn. In: Proceedings of the 20th World Congress of Philosophy. Boston. August.Google Scholar
  48. Ryle, G. 1953. Ordinary language. Philosophical ReviewLXII.Google Scholar
  49. Ryle, G. 1971. Ordinary language. In: G. Ryle, Collected Papers. London: Hutchinson.Google Scholar
  50. Sacks, O. 2005. Recalled to Life. The New Yorker, October 31.Google Scholar
  51. Sowa, J.F. 2000. Knowledge Representation: Logical, Philosophical, and Computational Foundations. Pacific Grove, CA: Brooks Cole Publishing Co.Google Scholar
  52. Stetina, J., S. Kurohashi and M. Nagao. 1998. General word sense disambiguation method based on a full sentential context. In: Proceedings of the COLING-ACL Workshop on the Usage of WordNet in Natural Language Processing Systems. Montreal.Google Scholar
  53. Viegas, E., Onyshkevych, B., Raskin, V. and S. Nirenburg. 1996. From Submit to Submitted via Submission: On lexical rules in large-scale lexicon acquisition. In: Proceedings of ACL-96.Google Scholar
  54. Vieira, R. and M. Poesio. 2000. Processing definite descriptions in corpora. In: S. Botley and T. McEnery (Eds.), Corpus-based and Computational Approaches to Anaphora. Benjamins, Amsterdam.Google Scholar
  55. Watzka, H. 2002. Did Wittgenstein ever take the linguistic turn? Revista Portuguesa de Filosofia, 58.Google Scholar
  56. Weinreich, U. 1966. Explorations in semantic theory. In: T.A. Sebeok (Ed.), Current Trends in Linguistics. Vol. III. The Hague: Mouton.Google Scholar
  57. Wilks, Y. 1968. Argument and Proof in Metaphysics, from an empirical point of view. Unpublished PhD thesis (Professor R.B. Braithwaite), University of Cambridge.Google Scholar
  58. Wilks, Y. 1975. A preferential pattern-matching semantics for natural language. Artificial Intelligence, 6: 53–74.CrossRefGoogle Scholar
  59. Wilks, Y. 1977. Making preferences more active. Artificial Intelligence, 11: 197–223CrossRefGoogle Scholar
  60. Wilks, Y. 2001. Fodor – “Fodor” strikes back. In: F. Busa and P. Bouillon. The Language of Word Meaning. Cambridge, UK: Cambridge University Press.Google Scholar
  61. Wilks, Y. 2002. Ontotherapy or how to stop worrying about what there is, Invited presentation, Ontolex 2002, Workshop on Ontologies and Lexical Knowledge Bases, 27th May, Held in conjunction with the Third International Conference on Language Resources and Evaluation – LREC02, 29–31 May, Las Palmas, Canary Islands.Google Scholar
  62. Wilks, Y., B. Slator and L. Guthrie. 1996. Electric Words: Dictionaries, Computers and Meanings. Cambridge, MA: MIT Press.Google Scholar
  63. Wilks, Y. and M. Stevenson. 1997. Sense tagging: semantic tagging with a lexicon. In: Proceedings of ANLP-97. Washington, DC.Google Scholar
  64. Wittgenstein, L. 1953. Philosophical Investigations. Oxford: Blackwell.Google Scholar
  65. Woods, W. 1975. What’s in a Link: Foundations for semantic networks. In: D. Bobrow and A. Collins (Eds.), Representation and Understanding: Studies in Cognitive Science. New York: Academic Press.Google Scholar

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© Springer 2007

Authors and Affiliations

  1. 1.Institute for Language and Information TechnologiesUniversity of MarylandBaltimore CountyUSA

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