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Reanalysis and Limited Repair Parsing: Leaping off the Garden Path

  • Richard L. Lewis
Part of the Studies in Theoretical Psycholinguistics book series (SITP, volume 21)

Abstract

This chapter develops a theory of reanalysis called limited repair parsing. Repair parsers deal with the problem of local ambiguity in part by modifying previously built structure when the chosen structure later proves to be inconsistent. This modification of existing structure distinguishes repair parsing from parallel or multi-path parsing, least-commitment parsing, backtracking, or reparsing strategies. Parsers with a limited capability for repair are psycholinguistically important because they can potentially explain the contrasts between difficult garden path structures (when repair fails) and unproblematic local ambiguities (when repair is successful or easy). Although the idea of repair has been implicit in some psycholinguistic work (and emerged explicitly in the diagnosis model of Fodor & Inoue, 1994, and the NL-Soar model of Lewis, 1993), there has been no clear formulation of the general class of repair parsers. This chapter makes a first step toward such a formulation, shows how repair parsing offers significant computational advantages over other alternatives for reanalysis, and proposes a particular repair mechanism, snip, that explains a wide range of cross-linguistic reanalysis phenomena. Snip is a proposal for a simple, automatic, on-line repair process. The chapter concludes by briefly describing how snip can be embedded in a more comprehensive sentence processing architecture that maintains the structural sensitivity of purely syntactic theories like Pritchett’s (1992), yet still accounts for the flexibility of parsing as revealed by interactive studies.

Keywords

Relative Clause Ambiguity Resolution Parse Tree Sentence Comprehension Sentence Processing 
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. Abney, S.P. 1989. A computational model of human parsing. Journal of Psycholinguistic Research, 18, 1, 129–144.CrossRefGoogle Scholar
  2. Altmann, G. and Steedman, M. 1988. Interaction with context during human sentence processing. Cognition, 30, 191–238.CrossRefGoogle Scholar
  3. Bever, T.G. 1970. The cognitive basis for linguistic structures. In J.R. Hayes (ed.), Cognition and the Development of Language. New York, NY: Wiley, 279–362.Google Scholar
  4. Blank, G.D. 1989. A finite and real-time processor for natural language. Communications of the ACM, 32, 10, 1174–1189.CrossRefGoogle Scholar
  5. Carpenter, P.A. and Daneman, M. 1981. Lexical retrieval and error recovery in reading: A model based on eye fixations. Journal of Verbal Learning and Verbal Behavior, 20, 137–160.CrossRefGoogle Scholar
  6. Crain, S. and Steedman, M. 1985. On not being led up the garden path: The use of context by the psychological syntax processor. In D.R. Dowty, L. Karttunen, and A.M. Zwicky (eds.), Natural Language Parsing. Cambridge, U.K.: Cambridge University Press, 320–358.Google Scholar
  7. Ferreira, F. and Henderson, J.M. 1990. Use of verb information in syntactic parsing: Evidence from eye movements and word-by-word self-paced reading. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16, 555–568.Google Scholar
  8. Ferreira, F. and Henderson, J.M. 1991. Recovery from misanalyses of garden-path sentences. Journal of Memory and Language, 30, 725–745.CrossRefGoogle Scholar
  9. Fodor,J.DandInoue,A. 1994. The diagnosis and cure of garden paths.Jounal of Psycholinguistic Research, 23, 407–434.Google Scholar
  10. Fong, S. and Berwick, R. 1990. The computational implementation of principle-based parsers. In M. Tomita (ed.), Proceedings of the First International Workshop on Parsing Technologies. Pittsburgh, PA: Carnegie Mellon University, 75–84.Google Scholar
  11. Frazier, L. 1978. On Comprehending Sentences: Syntactic Parsing Strategies. Unpublished doctoral dissertation, University of Connecticut, Storrs, CT. Distributed by the Indiana University Linguistics Club, Bloomington, IN.Google Scholar
  12. Frazier, L. and Rayner, K. 1982. Making and correcting errors during sentence comprehension: Eye movements in the analysis of structurally ambiguous sentences, Cognitive Psychology 14, 178–210.CrossRefGoogle Scholar
  13. Gathercole, S.E. and Baddeley, A.D. 1993. Working Memory and Language. Hove, UK: Lawrence Erlbaum Associates.Google Scholar
  14. Gibson, E.A.F. 1991. A Computational Theory of Human Linguistic Processing: Memory Limitations and Processing Breakdown. Unpublished doctoral dissertation, Carnegie Mellon University, Pittsburgh, PA. Available as Center for Machine Translation Technical Report CMU-CMT-91–125.Google Scholar
  15. Godden, K. 1990. Lazy unification. Association for Computational Linguistics, 28, 180–187.Google Scholar
  16. Gorrell, P 1993. Incremental structure building and the determinism hypothesis. Paper presented at Sixth Annual CUNY Conference on Human Sentence Processing, Amherst, MA.Google Scholar
  17. Gorrell, P. 1991. Subcategorization and sentence processing. In R.C. Berwick, S.P. Abney, and C. Tenny (eds.), Principle Based Parsing: Computation and Psycholinguistics. Dordrecht: Kluwer Academic Publishers, 279–300.CrossRefGoogle Scholar
  18. Gorrell, P. 1987. Studies of Human Syntactic Processing: Ranked-Parallel versus Serial Models. Unpublished doctoral dissertation, University of Connecticut, Storrs, CT.Google Scholar
  19. Holbrook, J.K., Eiselt, K.P., and Mahesh, K. 1992. A unified process model of syntactic and semantic error recovery in serntence understanding. In Proceedings of the 14th Annual Conference of the Cognitive Science Society, 195–200.Google Scholar
  20. Inoue, A. and Fodor, J.D. 1995. Information-paced parsing of Japanese. In R. Mazuka and N. Nagai (eds.), Japanese Sentence Processing. Hillsdale, NJ: Lawrence Erlbaum Associates, 9–63.Google Scholar
  21. Juliano, C. and Tanenhaus, M.K. 1994. A constraint-based lexicalist account of the subject/object attachment preference. Journal of Psycholinguistic Research, 23, 6, 459–471.CrossRefGoogle Scholar
  22. Just, M.A. and Carpenter, P.A. 1992. A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 1, 122–149.CrossRefGoogle Scholar
  23. Kaplan, R. 1972. Augmented transition networks as psychological models of sentence comprehension. Artificial Intelligence, 3, 77–100.CrossRefGoogle Scholar
  24. King, J. and Just, M.A. 1991. Individual differences in syntactic processing: The role of working memory. Journal of Memory and Language, 30, 580–602.CrossRefGoogle Scholar
  25. Konieczny, L. 1996. Human Sentence Processing: A Semantics-Oriented Parsing Approach. Unpublished doctoral dissertation, University of Freiburg.Google Scholar
  26. Kurtzman, H.S. 1985. Studies in Syntactic Ambiguity Resolution. Unpublished doctoral dissertation, MIT, Cambridge, MA.Google Scholar
  27. Laird, J.E. 1988. Recovery from incorrect knowledge in Soar. In Proceedings of the Seventh National Conference on Artificial Intelligence, The American Association for Artificial Intelligence, 618–623.Google Scholar
  28. Laird, J.E., Newell, A., and Rosenbloom, P.S. 1987. Soar: An architecture for general intelligence. Artificial Intelligence, 33, 1–64.CrossRefGoogle Scholar
  29. Lehman, J.F., Lewis, R.L., and Newell, A. 1991. Integrating knowledge sources in language comprehension. In Proceedings of the 13th Annual Conference of the Cognitive Science Society, 461–466. Also in P.S. Rosenbloom, J.E. Laird, and A. Newell (eds.), The Soar Papers: Research on Integrated Intelligence. Cambridge, MA: MIT Press, 1993, 1309–1314.Google Scholar
  30. Lewis, R.L. 1992. Recent developments in the NL-Soar garden path theory. Technical Report CMU-CS-92–141, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
  31. Lewis, R.L. 1993a. An Architecturally-Based Theory of Human Sentence Comprehension. Unpublished doctoral dissertation, Carnegie Mellon University, Pittsburgh, PA. Available as Technical Report CMU-CS-93–226 from reports@cs.cmu.edu.Google Scholar
  32. Lewis, R.L. 1993b. An architecturally-based theory of sentence comprehension. In Proceedings of the 15th Annual Conference of the Cognitive Science Society, 108–113.Google Scholar
  33. Lewis, R.L. 1996a. Architecture matters: What Soar has to say about modularity. In D. Steier and T. Mitchell (eds.), Mind Matters: Contributions to Cognitive and Computer Science in Honor of Allen Newell. Hillsdale, NJ: Lawrence Erlbaum, 75–84.Google Scholar
  34. Lewis, R.L. 1996b. Interference in short-term memory: The magical number two (or three) in sentence processing. Journal of Psycholinguistic Research, 25, I, 93–115.Google Scholar
  35. Lewis, R.L. and Lehman, J.F. 1994. A theory of the computational architecture of sentence comprehension. Unpublished manuscript, Cognitive Science Laboratory, Princeton University, Princeton, NJ.Google Scholar
  36. Lombardo, V. (this volume). A computational model of recovery.Google Scholar
  37. Lytinen, S.L. and Tomuro, N. 1996. Left-corner unification-based natural language processing. In Proceedings of the 13th National Conference on Artificial Intelligence. The American Association for Artificial Intelligence, 1037–1043.Google Scholar
  38. MacDonald, M.C., Pearlmutter, N.J., and Seidenberg, M.S. 1994. The lexical nature of syntactic ambiguity resolution. Psychological Review, 101, 676–703.CrossRefGoogle Scholar
  39. Marcus, M.P. 1980. A Theory of Syntactic Recognition for Natural Language. Cambridge, MA: MIT Press.Google Scholar
  40. Mazuka, R., Itoh, K., Kiritani, S., Niwa, S., Ikejiru, K., and Naitoh, K. 1989. Processing of Japanese garden path, center-embedded, and multiply left-embedded sentences. Annual Bulletin of the Research Institute of Logopedics and Phoniatrics, Vol. 23. University of Tokyo, 187–212.Google Scholar
  41. McCawley, J.D. 1988. The Syntactic Phenomena of English, Vol. 1. Chicago, IL: University of Chicago Press.Google Scholar
  42. Milne, R.W. 1982. Predicting garden path sentences. Cognitive Science, 6, 349–373.CrossRefGoogle Scholar
  43. Minton, S., Johnston, M.D., Philips, A.B., and Laird, P. 1992. Minimizing conflicts: A heuristic repair method for constraint satisfaction and scheduling problems. Artificial Intelligence, 58, 161–205.CrossRefGoogle Scholar
  44. Mitchell, D. 1987. Lexical guidance in human parsing: Locus and processing characteristics. In M. Coltheart (ed.), The Psychology of Reading, Attention and Performance, Vol. 12. Hillsdale, NJ: Lawrence Erlbaum, 601–681.Google Scholar
  45. Nadel, B.A. 1990. Representation selection for constraint satisfaction: A case study using n-queens. IEEE Expert, 16–23.Google Scholar
  46. Newell, A. 1990. Unified Theories of Cognition. Cambridge, MA: Harvard University Press.Google Scholar
  47. Pritchett, B.L. 1988. Garden path phenomena and the grammatical basis of language processing. Language, 64, 539–576.CrossRefGoogle Scholar
  48. Pritchett, B.L. 1991. Head position and parsing ambiguity. Journal of Psycholinguistic Research, 20, 251–270.CrossRefGoogle Scholar
  49. Pritchett, B.L. 1992. Grammatical Competence and Parsing Performance. Chicago, IL: University of Chicago Press.Google Scholar
  50. Rayner, K., Carlson, M., and Frazier, L. 1983. The interaction of syntax and semantics during sentence processing: Eye movements in the analysis of semantically biased sentences. Journal of Verbal Learning and Verbal Behavior, 22, 358–374.CrossRefGoogle Scholar
  51. Sosic, R. and Gu, J. 1990. A polynomial time algorithm for the n-queens problem. SIGART Bulletin, 1, 3, 7–11.CrossRefGoogle Scholar
  52. Stevenson, S. 1994. Competition and recency in a hybrid network model of syntactic disambiguation. Journal of Psycholinguistic Research, 23, 4, 295–322.CrossRefGoogle Scholar
  53. Stowe, L. 1986. Evidence for on-line gap location. Language and Cognitive Processes, 1, 277–245.CrossRefGoogle Scholar
  54. Sturt, P. and Crocker, M. 1995. Monotonic parsing and reanalysis. Paper presented at Eighth Annual CUNY Sentence Processing Conference, Tucson, AZ.Google Scholar
  55. Trueswell, J.C., Tanenhaus, M.K., and Garnsey, S.M. 1994. Semantic influences in parsing: Use of thematic role information in syntactic ambiguity resolution. Journal of Memory and Language, 33, 285–318.CrossRefGoogle Scholar
  56. Wanner, E. and Maratsos, M. 1978. An ATN approach to comprehension. In M. Halle, J. Bresnan, and G.A. Miller (eds.), Linguistic Theory and Psychological Reality. Cambridge, MA: MIT Press, 119–161.Google Scholar
  57. Warner, J. and Glass, A.L. 1987. Context and distance-to-disambiguation effects in ambiguity resolution: Evidence from grammaticality judgments of garden path sentences. Journal of Memory and Language, 26, 714–738.CrossRefGoogle Scholar
  58. Weinberg, A. 1993. Parameters in the theory of sentence processing: Minimal commitment theory goes east. Journal of Psycholinguistic Research, 22, 3, 339–364.CrossRefGoogle Scholar
  59. Winograd, T. 1972. Understanding natural language. Cognitive Psychology, 3, 1–191.CrossRefGoogle Scholar
  60. Winograd, T. 1983. Language as a Cognitive Process, Vol. 1: Syntax. Reading, MA: Addison Wesley.Google Scholar
  61. Winston, P.H. 1992. Artificial Intelligence, Third Edition. Reading, MA: Addison Wesley.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1998

Authors and Affiliations

  • Richard L. Lewis
    • 1
  1. 1.The Ohio State UniversityUSA

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