Simple-english for data base communication

  • J. A. Moyne
Article
Received:
Revised:

Abstract

Three classes of the so-called natural languages for communication with data bases are defined:English-like, pseudo-English, andsimple-English. It is argued that English-like and pseudo-English languages are normally more difficult to learn and use than artificial programming languages with no overt claim to English likeness. Simple-English is presented as a family of languages in which many restrictions (which hamper learning) are removed through interaction with, and drawing inferences from, the data base and the underlying system. It is concluded, however, that English likeness and ease of learning may be contradictory notions.

Key words

Ambiguity problems data base communication data base models English-like and pseudo-English languages learning problems linguistics narrative languages semantics simple-English 
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Y. Bar-HillelLanguage and Information (Addison-Wesley, Reading, Mass., 1964).Google Scholar
  2. 2.
    D. G. Bobrow and B. Raphael, “New programming languages for artificial intelligence research,”ACM Comput. Rev. 6 (3):153–174 (September 1974).Google Scholar
  3. 3.
    Center for Applied Linguistics,Research Trends in Computational Linguistics (Center for Applied Linguistics, Washington, D.C., 1972).Google Scholar
  4. 4.
    N. Chomsky,Aspects of the Theory of Syntax (MIT Press, Cambridge, Mass., 1965).Google Scholar
  5. 5.
    Feature Analysis of Generalized Data Base Management Systems, CODASYL Systems Committee, ACM, New York (May 1971).Google Scholar
  6. 6.
    P. Culicover, J. Kimball, D. Lewis, D. Loveman, and J. Moyne, “An Automated Recognition Grammar for English,” Technical Report FSC 69-5007, IBM, Cambridge, Mass. (1969).Google Scholar
  7. 7.
    C. Hewitt, “PLANNER, A Project MAC report,” MAC-M-386, MIT, Cambridge, Mass. (October 1968); revised August 1970.Google Scholar
  8. 8.
    D. E. Knuth, “Structured programming with go to statements,”ACM Comput. Surv. 6(4):261–301 (December 1974).Google Scholar
  9. 9.
    F. W. Lancaster and E. G. Fayen,Information Retrieval On-Line (Melville, Los Angeles, 1973).Google Scholar
  10. 10.
    D. B. Loveman, J. A. Moyne, and R. G. Tobey, “Cue: A Processor System for Restricted Natural English,”Proceedings of the Symposium on Information Storage and Retrieval University of Maryland (1971), pp. 47–59.Google Scholar
  11. 11.
    C. A. Montgomery, “Linguistics and information science,”J. Am. Soc. Inf. Sci. (May–June 1972), pp. 195–219.Google Scholar
  12. 12.
    J. A. Moyne, “A Simulated Computer for Natural Language Processing,” Technical Report TR 00.1463, IBM (1966).Google Scholar
  13. 13.
    J. A. Moyne, “Introduction to an Operational RELADES,” Technical Report TR 00.1442, IBM (1966).Google Scholar
  14. 14.
    J. A. Moyne, “Proto-RELADES: A Restrictive Natural Language System,” Technical Report BPC 3, IBM, Cambridge, Mass. (1967).Google Scholar
  15. 15.
    J. A. Moyne, “An introduction to transformational grammars,”Int. J. Comput. Math. 2:169–181 (1968).Google Scholar
  16. 16.
    J. A. Moyne, “Informational retrieval and natural language,”Proc. Am. Soc. Inf. Sci. 6:259–263 (1969).Google Scholar
  17. 17.
    J. A. Moyne, “Some Grammars and Recognizers for Formal and Natural Languages,” inAdvances in Information Systems Science, Julius T. Tou, Ed. (Plenum, New York, 1974).Google Scholar
  18. 18.
    M. Pacak and A. W. Pratt, “The Function of Semantics in Automated Language Processing,Proceedings of the Symposium on Information Storage and Retrieval, University of Maryland (1971), pp. 5–18.Google Scholar
  19. 19.
    R. Rustin, Ed.,Natural Language Processing (Algorithmics Press, New York, 1973).Google Scholar
  20. 20.
    G. Salton,Automatic Information Organization and Retrieval (McGraw-Hill, New York, 1968).Google Scholar
  21. 21.
    J. E. Sammet,Programming Languages: History and Fundamentals (Prentice-Hall, Englewood Cliffs, N.J., 1969).Google Scholar
  22. 22.
    S. Y. Sedelow and W. A. Sedelow,Language Research and the Computer (The University of Kansas, Lawrence, 1972).Google Scholar
  23. 23.
    R. M. Schwarcz, J. F. Burger, and R. F. Simmons, “A deductive question-answering for natural language inference,”Commun. ACM,13 (3):167–183 (March 1970).Google Scholar
  24. 24.
    “SIGPLAN, Proceedings of a symposium on very high level languages,”SIGPLAN Notices,ACM:9(4) (April 1974).Google Scholar
  25. 25.
    G. J. Sussman, and D. V. McDermott, “From conniver to planner, a genetic approach,”Proc. FJCC (1972).Google Scholar
  26. 26.
    D. E. Walker, “Automated Language Processing,” inAnnual Review of Information Science and Technology, Vol. 8, Carios A. Cuadra, Ed. (American Society for Information Science, Washington, D.C., 1973).Google Scholar
  27. 27.
    T. Winograd,Understanding Natural Languages (Academic Press, New York, 1972).Google Scholar
  28. 28.
    W. A. Woods, “Semantics for a Question-Answering System,” Report No. NSF 19 to National Science Foundation, Harvard University, Cambridge, Mass. (1967).Google Scholar
  29. 29.
    W. A. Woods, R. M. Kaplan, and B. Nash-Webber, “The Lunar Sciences Natural Language Information System: Final Report,” BBN Report No. 2378, Bolt Beranek and Newman, Cambridge, Mass. (1972).Google Scholar
  30. 30.
    V. Yngve,COMIT, 2nd ed. (MIT Press, Cambridge, Mass.).Google Scholar

Copyright information

© Plenum Publishing Corporation 1977

Authors and Affiliations

  • J. A. Moyne
    • 1
  1. 1.Department of Computer ScienceQueens College of The City University of New YorkFlushing

Personalised recommendations