Robust Parsing Using Multiple Construction-Specific Strategies

  • J. G. Carbonell
  • P. J. Hayes
Part of the Symbolic Computation book series (SYMBOLIC)


Robust natural language interpretation requires strong semantic domain models, “fail-soft” recovery heuristics, flexible control structures, and focused user interaction when automatic correction proves unfeasible. Although single-strategy parsers have met with some success, a multi-strategy approach, with strategies selected dynamically according to the type of construction being parsed at any given time, is shown to provide a higher degree of flexibility, redundancy, and ability to bring task-specific domain knowledge (in addition to general linguistic knowledge) to bear on both grammatical and ungrammatical input. This construction-specific, multi-strategy approach can also help provide tightly focused interaction with the user in cases of semantic or structural ambiguity by allowing such ambiguities to be represented without duplication of unambiguous material. The approach also aids in task-specific language development by allowing direct interpretation of languages defined in terms natural to the task domain, and with the definition of data base interfaces by facilitating a unified treatment of update and access requests. Two small experimental parsers that were implemented to illustrate these advantages are presented, followed by the description of a parsing algorithm that integrates several of the best features of the two smaller parsers, including case-frame instantiation and partial pattern-matching strategies. The algorithm can deal with conjunctions, fragmentary input, and ungrammatical structures, as well as less exotic, grammatically correct input.


Noun Phrase Case Filler Computational Linguistics Case Marker Structural Ambiguity 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ball, J. E. and Hayes, P.J.: Representation of Task-Independent Knowledge in a Gracefully Interacting User Interface. Proc reedings of the 1st Annual Meeting of the American Association for Artificial Intelligence, Stanford University, August 1980, pp.116–120Google Scholar
  2. 2.
    Birnbaum, L. and Selfridge, M.: Conceptual Analysis in Natural Language. In: Schank, R. and Riesbeck, C. (eds.): Inside Computer Understanding. New Jersey: Erlbaum 1980, pp.318–353Google Scholar
  3. 3.
    Burton, R. R.: Semantic Grammar. An Engineering Technique for Constructing Natural Language Understanding Systems. Technical Report 3453. Bolt, Beranek, and Newman, Inc., Cambridge, Mass., 1975Google Scholar
  4. 4.
    Carbonell, J. G.: Towards a Self-Extending Parser. Proceedings of the 17th Meeting of the Association for Computational Linguistics, 1979, pp.3–7Google Scholar
  5. 5.
    Carbonell, J. G.: A-MIN: A Search-Control Method for Information-Gathering Problems. Proceedings of the First AAAI Conference, August 1980Google Scholar
  6. 6.
    Carbonell, J. G. and Hayes, R J.: Dynamic Strategy Selection in Flexible Parsing. Proceedings of the 19th Annual Meeting of the Association for Computational Linguistics, Stanford University, June 1981, pp.143–147Google Scholar
  7. 7.
    Carbonell, J. G.: POLITICS: An Experiment in Subjective Understanding and Integrated Reasoning. In: Schank, R. C. and Riesbeck, C. K. (eds.): Inside Computer Understanding: Five Programs Plus Miniatures. New Jersey: Erlbaum, 1981Google Scholar
  8. 8.
    Carbonell, J. G., Boggs, W. M., Mauldin, M. L., and Anick, R. G.: The XCALIBUR Project, A Natural Language Interface to Expert Systems. Proceedings of the Eighth International Joint Conference on Artificial Intelligence, 1983Google Scholar
  9. 9.
    Carbonell, J. G., Boggs, W. M., Mauldin, M. L., and Anick, P. G.: XCALIBUR Progress Report No.1: First Steps Towards an Integrated Natural Language Interface. Technical Report. Carnegie-Mellon University, Computer Science Department, Karlsruhe, 1983Google Scholar
  10. 10.
    Carbonell, J. G.: Robust Man-Machine Communication, User Modelling and Natural Language Interface Design. In: Andriole, (ed.): Applications in Artificial Intelligence. Petrocelli Books Inc. 1983Google Scholar
  11. 11.
    ACM Publications: Data Base Task Group of CODASYL Programming Language Committee Report, NY, 1971Google Scholar
  12. 12.
    Gershman, A.V.: Knowledge-Based Parsing. Ph. D. Dissertation. Yale University, April 1979, Computer Science Department Report No.156Google Scholar
  13. 13.
    Haas, N. and Hendrix G. G.: Learning by Being Told: Acquiring Knowledge for Information Management. In: Michalski, R. S., Carbonell, J. G., and Mitchell, T. M. (eds.): Machine Learning, An Artificial Intelligence Approach. Palo Alto: Tioga Press 1983Google Scholar
  14. 14.
    Hayes, P. J., Ball, J. E., and Reddy, R.: Breaking the Man-Machine Communication Barrier. Computer 14 (3), March 1981Google Scholar
  15. 15.
    Hayes, P. J. and Mouradian, G. V.: Flexible Parsing. Proceedings of the 18th Annual Meeting of the Association for Computational Linguistics, Philadelphia, June 1980, pp.97–103Google Scholar
  16. 16.
    Hayes, P.J. and Reddy, R.: An Anatomy of Graceful Interaction in Man-Machine Communication. Technical Report. Computer Science Department, Carnegie-Mellon University, 1979Google Scholar
  17. 17.
    Hendrix, G.G., Sacerdoti, E. D., and Slocum, J.: Developing a Natural Language Interface to Complex Data. Technical report. Artificial Intelligence Center, SRI International, 1976Google Scholar
  18. 18.
    Hendrix, G. G.: Human Engineering for Applied Natural Language Processing. Proceedings of the Fifth International Joint Conference on Artificial Intelligence, 1977, pp.183–191Google Scholar
  19. 19.
    Hendrix, G. G.: The LIFER Manual: A Guide to Building Practical Natural Language Interfaces. Technical Report, Technical Note 138. SRI International, 1977Google Scholar
  20. 20.
    Kaplan, S. J.: Cooperative Responses from a Portable Natural Language Data Base Query System. Ph. D. Dissertation. Department of Computer and Information Science, University of Pennsylvania, Philadelphia, 1979Google Scholar
  21. 21.
    Kaplan, S.J.: Interpreting Natural Language Data Base Updates. Submitted for the 19th Annual Meeting of the Association for Computational Linguistics, Stanford University, June 1981Google Scholar
  22. 22.
    Kwasny, S.C. and Sondheimer, N. K.: Ungrammatically and Extra-Grammaticality in Natural Language Understanding Systems. Proceedings of the 17th Annual Meeting of the Association for Computational Linguistics, La Jolla, CA, August 1979, pp.19–23Google Scholar
  23. 23.
    Marcus, M.P.: A Theory of Syntactic Recognition for Natural Language. Cambridge: MIT Press 1980MATHGoogle Scholar
  24. 24.
    McDermott, J.: XSEL: A Computer Salesperson’s Assistant. In: Hayes, J., Michie, D., and Pao, Y.-H. (eds.): Machine Intelligence 10. Chichester, UK: Ellis Horwood 1982, pp.325–337Google Scholar
  25. 25.
    Parkison, R.C. Colby, K. M. and Faught, W. S.: Conversational Language Comprehension Using Integrated Pattern-Matching and Parsing. Artificial Intelligence 9, 111–134 (1977)MATHCrossRefGoogle Scholar
  26. 26.
    Riesbeck, C. and Schank, R. C.: Comprehension by Computer: Expectation-Based Analysis of Sentences in Context. Technical Report 78. Computer Science Department, Yale University 1976Google Scholar
  27. 27.
    Sacerdoti, E. D.: Language Access to Distributed Data with Error Recovery. Proceedings of the Fifth International Joint Conference on Artificial Intelligence, 1977, pp.196–202Google Scholar
  28. 28.
    Waltz, D. L. and Goodman, A.B.: Writing a Natural Language Data Base System. Proceedings of the Fifth International Joint Conference on Artificial Intelligence, 1977, pp.144–150Google Scholar
  29. 29.
    Weischedel, R. M. and Black, J.: Responding to Potentially Unparseable Sentences. American Journal of Computational Linguistics 6, 97: 109 (1980)Google Scholar
  30. 30.
    Woods, W.A., Kaplan, R. M., and Nash-Webber, B.: The Lunar Sciences Language System: Final Report. Technical Report 2378. Bolt, Beranek, and Newman, Inc., Cambridge, Mass., 1972Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1987

Authors and Affiliations

  • J. G. Carbonell
  • P. J. Hayes

There are no affiliations available

Personalised recommendations