Capability based natural language understanding

  • A. Jennings
  • C. D. Rowles
Natural Language
Part of the Lecture Notes in Computer Science book series (LNCS, volume 406)


There are many natural language systems that aim for generality. This paper describes a different approach where the language system is virtually embedded with the applications to which it is intended to deliver the parsed language. Whilst at first this may appear to be a step backwards, it has many pragmatic advantages in dealing with ill-formed input, jargon and ellipsis. By limiting natural language interaction to a narrow corridor, we maintain a strong focus for potential dialogues. This strong focus also provides the ability to readily assimilate new word meanings.

Keywords and phrases

natural language understanding semantics word learning 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

8. References

  1. Ayuso, D.M. et al "An Environment for Acquiring Semantic Information" Proceedings of the 25th Annual Meeting of the ACL, pp. 32–40, 1987.Google Scholar
  2. Ballard, B. W & Stumberger, D.E. "Semantic Acquisition in TELI" Proceedings of the 24th Annual Meeting of the ACL, pp. 20–29, 1986.Google Scholar
  3. Binot, J-L & Jensen, K. "A Semantic Expert Using an On-line Standard Dictionary" IJCAI87, pp. 709–714.Google Scholar
  4. Carbonell, J.G & Hayes, P.J. "Recovery Strategies for Parsing Extragrammatical Language" American Journal of Computational Linguistics, 9, pp. 123–146, 1983.Google Scholar
  5. Carbonell, J.G. & Hayes, P.J. "Robust Parsing Using Multiple Construction-Specific Strategies" in Natural Language Parsing Systems, L. Bolc (Editor), Springer-Verlag, 1987.Google Scholar
  6. Cullingford, R.E. Natural Language Processing: A Knowledge Engineering Approach, Rowman & Littlefield, New Jersey 1986.Google Scholar
  7. Dik, S.C "Linguistically Motivated Knowledge Representation" in Language and Artificial Intelligence, M.Nagao (Editor), Elsevier Science Publishers B.V. (North-Holland), 1987.Google Scholar
  8. Furnas, G.W. et al "The Vocabulary Problem in Human-System Communication" Communications of the ACM, 30, pp. 964–971, 1987.Google Scholar
  9. Granger, R.H. "FOUL-UP: A Program that Figures Out Meanings of Words from Context" IJCAI77, pp. 172–178.Google Scholar
  10. Guo, Cheng-ming "Interactive Vocabulary Acquisition in XTRA" IJCAI87, pp. 715–717.Google Scholar
  11. Hirst, G. "Semantic Interpretation and Ambiguity" Artificial Intelligence, 34, pp. 131–177, 1988.Google Scholar
  12. Hendrix, G.G. et al "Developing a Natural Language Interface to Complex Data" SRI Technical Note 152, 1977.Google Scholar
  13. Keller, R.M. "Defining Operationality for Explanation-Based Learning" AAAI87, pp. 482–487Google Scholar
  14. Lebowitz, M. "Memory-Based Parsing" Artificial Intelligence, 21, pp. 363–404, 1983.Google Scholar
  15. Lenat, D. et al "CYC: Using Commonsense Knowledge to Overcome Brittleness and Knowledge Acquisition Bottlenecks" The AI Magazine, Winter 1986, pp. 65–85.Google Scholar
  16. Litman, D. "Plan Recognition and Discourse Analysis: An Integrated Approach for Understanding Dialogues" PhD Thesis, University of Rochester, NY 1985.Google Scholar
  17. Mooney, R.J. "A General Explanation-Based Learning Mechanism and its Application to Narrative Understanding" University of Illinois at Urbana-Champaign Technical Report UILU-ENG-87-2269, 1988.Google Scholar
  18. Selfridge, M. "A Computer Model of Child Language Learning" Artificial Intelligence, 29, pp. 171–216, 1986.Google Scholar
  19. Wilks, Y. "A Preferential, Pattern-Seeking, Semantics for Natural Language Inference" Artificial Intelligence, 6, pp. 53–74, 1975.Google Scholar
  20. Winograd, T. Language as a Cognitive Process, Addison-Wesley 1983.Google Scholar
  21. Winograd, T. "A Language/Action Perspective on the Design of Cooperative Work" to appear in Human-Computer Interaction 1987Google Scholar
  22. Zernik, Uri "Learning Idioms — With and Without Explanation" IJCAI87, pp. 133–136, 1987.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • A. Jennings
    • 1
  • C. D. Rowles
    • 1
  1. 1.Artificial Intelligence Technology SectionTelecom Australia ResearchClayton

Personalised recommendations