Machine Translation

, Volume 10, Issue 4, pp 269–291 | Cite as

A model of a bi-directional transfer mechanism using rule combinations

  • Hideo Watanabe


This paper proposes a new type of transfer mechanism, called Rule Combination Transfer (or RCT), that produces an output structure by non-destructively combining target parts of translation rules, each of which consists of dependency structures in source and target languages and correspondences between them. This proposed mechanism employs more extended mapping of correspondences than one-to-one mapping used in conventional transfer systems, to allow expression of some peculiar or exceptional translation phenomena. Further, these translation rules can be used bi-directionally. Although, the proposed transfer mechanism is intended to be a foundation for an example-based transfer system by coupling it with a mechanism selecting translation rules based on the similarity with an input, it can be also used as a foundation for a conventional transfer system.

Key words

Machine translation transfer system example-based approach 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abeillé, A., Schabes, Y., and Joshi, A. K., Using lexicalized tags for machine translation,Proc. of Coling, 90: 1990.Google Scholar
  2. 2.
    Boitet, C. and Nedobejkine, N., Recent development in Russian-French machine translation at Grenoble,Linguistics, 19: 199–271, 1981.Google Scholar
  3. 3.
    Ait-Kaci, H., An algebraic semantics approach to the effective resolution of type equations,Theoretical Computer Science, 45: 293–351, 1986.Google Scholar
  4. 4.
    Ehrig, H., Introduction to the algebraic theory of graph grammaers,Proc. Int. Workshop on Graph Grammars, LNCS 73: 1–69, 1979.Google Scholar
  5. 5.
    Furuse, O. and Ida, H., Cooperation between transfer and analysis in example-based framework,Proc. of Coling, 92, Vol. 2, pp. 645–651, 1992.Google Scholar
  6. 6.
    Gazar, G., Klein, E., Pullum, G. K., and Sag, I. A.,Generalized Phrase Structure Grammar, Harvard University Press, 1985.Google Scholar
  7. 7.
    Hutchings, W. J. (ed),Machine Translation: Past, Present, Future, pp. 239–248, Ellis Horwood Ltd., 1986.Google Scholar
  8. 8.
    Kaplan, R. and Bresnan, J., Lexical functional grammar: a formal system for grammatical representation, (J. Bresnan, ed),The Mental Representation of Grammatical Relations, MIT Press, Cambridge, MA, pp. 173–281, 1982.Google Scholar
  9. 9.
    Kay, M., Parsing in functional unification grammar,Psychological, Computational and Theoretical Perspectives, 251–278, 1985.Google Scholar
  10. 10.
    Knight, K., Unification: a multidisciplinary survey,ACM Computing Surveys, 21: No. 1, March 1989.Google Scholar
  11. 11.
    Kolodner, J. and Riesbeck, C., Case-based reasoning, tutorial textbook of 11th IJCAI, 1989.Google Scholar
  12. 12.
    Kudo, I. and Nomura, H., Lexical-functional transfer: a transfer framework in a machine translation system based on LFG,Proc. Coling, 86: 1986.Google Scholar
  13. 13.
    Nagao, M., A framework of a mechanical translation between japanese and english by analogy principle, Elithorn, A. and Banerji, R. (eds),Artificial and Human Intelligence, NATO, 1984.Google Scholar
  14. 14.
    Nagao, M. and Tsujii, J., The transfer phase of the mu machine translation system,Proc. Coling, 86: 1986.Google Scholar
  15. 15.
    Maruyama, H. and Watanabe, H., Tree cover search algorithm for example-based translation,Proc. 4th Int. Conf. on Theoretical and Methodological Issues in Machine Translation, 173–184, 1992.Google Scholar
  16. 16.
    Melby, A. K., Lexical transfer: a missing element in linguistic theories,Proc. Coling, 86: 104–106, 1986.Google Scholar
  17. 17.
    Nirenburg, S. (ed), Machine translation (special issue on knowledge-based machine translation, Part I), Vol. 4, No. 1, Kluwer, Dordrecht, 1989.Google Scholar
  18. 18.
    Nirenburg, S. (ed), Machine translation (special issue on knowledge-based machine translation, Part II), Vol. 4, No. 2, Kluwer, Dordrecht, 1989.Google Scholar
  19. 19.
    Nirenburg, S. (ed), Machine translation (special issue on EUROTRA I), Vol. 6, No. 2, Kluwer, Dordrecht, 1991.Google Scholar
  20. 20.
    Nirenburg, S. (ed), Machine translation (special issue on EUROTRA II), Vol. 6, NO. 3, Kluwer, Dordrecht, 1991.Google Scholar
  21. 21.
    Nitta, Y., Idiosyncratic gap: a though problem to structure-bound machine translation,Proc. Coling, 86: 107–111, 1986.Google Scholar
  22. 22.
    Perlmutter, D. M. (ed),Studies in Relational Grammar 1, University of Chicago Press, Chicago, 1983.Google Scholar
  23. 23.
    Perlmutter, D. M., and Rosen, C. G (eds),Studies in Relational Grammar 2, University of Chicago Press, Chicago, 1984.Google Scholar
  24. 24.
    Salder, V.,The Bilingual Knowledge Bank, BSO Research, March 1989.Google Scholar
  25. 25.
    Sato, S. and Nagao, M., Toward memory-based translation,Proc. Coling, 90: 1990.Google Scholar
  26. 26.
    Schenk, A., Idioms in the ROSETTA machine translation system,Proc. Coling, 86: 319–324, 1986.Google Scholar
  27. 27.
    Sowa, J. F.,Conceptual Structures: Information Processing in Mind and Machine, Addison-Wesley Publishing, 1984.Google Scholar
  28. 28.
    Sumita, E., Iida, H., and Kohyama, H., Translating with examples: a new approach to machine translation,Proc. Info. Japan, 90: 1990.Google Scholar
  29. 29.
    Tomita, M. and Carbonell, J. G., Another stride towards knowledge-based machine translation,Proc. Coling, 86: 1986.Google Scholar
  30. 30.
    Tsujii, J. and Fujita, K., Lexical transfer based on bilingual signs: towards interaction during transfer,Proc. Seoul Int. Conf. on NLP, 1990.Google Scholar
  31. 31.
    Watanabe, H., A model of transfer process using combinations of translation rules,Proc. Pacific Rim of Int. Conf. on AI'90, 1990.Google Scholar
  32. 32.
    Watanabe, H., A formal model of transfer using rules combinations,TRL Research Report RT0054, 1990.Google Scholar
  33. 33.
    Watanabe, H., A similarity-driven transfer system,Proc. Coling, 92: Vol. 2 770–776, 1992.Google Scholar
  34. 34.
    Watanabe, H., A method for extracting translation patterns from translation examples,Proc. 5th Int. Conf. Theoretical and Methodological Issues in Machine Translation, 292–301, 1993.Google Scholar
  35. 35.
    Watanabe, H. and Maruyama, H., A transfer system using example-based approach,IEICE Trans. Information and Systems, Vol. E77-D, No. 2, 247–257, Feb. 1994.Google Scholar

Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Hideo Watanabe
    • 1
  1. 1.Tokyo Research LaboratoryIBM ResearchKanagawa-kenJapan

Personalised recommendations