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Constituent Parsing

  • Pierre M. Nugues
Chapter
Part of the Cognitive Technologies book series (COGTECH)

Abstract

In the previous chapters, we used Prolog’s built-in search mechanism and the DCG notation to parse sentences and constituents. This search mechanism has drawbacks, however. To name some of them: its depth-first strategy does not handle left-recursive rules well, and backtracking is sometimes inefficient. In addition, if DCGs are appropriate to describe constituents, we haven’t seen means to parse dependencies until now.

Keywords

Noun Phrase Parse Tree Prepositional Phrase Grammar Rule Ambiguous Sentence 
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.

References

  1. Aho, A. V., Sethi, R., & Ullman, J. D. (1986). Compilers: Principles, techniques, and tools. Reading: Addison-Wesley.Google Scholar
  2. Allen, J. F. (1994). Natural language understanding (2nd ed.). Redwood City: Benjamin/ Cummings.Google Scholar
  3. Black, E., Abney, S., Flickenger, D., Gdaniec, C., Grishman, R., Harrison, P., Hindle, D., Ingria, R., Jelinek, F., Klavans, J., Liberman, M., Marcus, M., Roukos, S., Santorini, B., & Strzalkowski, T. (1991). A procedure for quantitatively comparing the syntactic coverage of English grammars. In Speech and natural language: Proceedings of a workshop, Pacific Grove (pp. 306–311). San Mateo: DARPA/Morgan Kaufmann.Google Scholar
  4. Charniak, E. (1993). Statistical language learning. Cambridge, MA: MIT.Google Scholar
  5. Charniak, E. (1997a). Statistical parsing with a context-free grammar and word statistics. In Proceedings of the fourteenth national conference on artificial intelligence, Providence. Menlo Park: AAAI/MIT.Google Scholar
  6. Charniak, E. (1997b). Statistical techniques for natural language parsing. AI Magazine, 18, 33–44.Google Scholar
  7. Charniak, E. (2000). A maximum-entropy-inspired parser. In Proceedings of the first meeting of the North American chapter of the ACL, Seattle (pp. 132–139).Google Scholar
  8. Charniak, E., Goldwater, S., & Johnson, M. (1998). Edge-based best-first chart parsing. In Proceedings of the sixth workshop on very large corpora, Montréal (pp. 127–133).Google Scholar
  9. Collins, M. J. (1999). Head-driven statistical models for natural language parsing. PhD thesis, University of Pennsylvania.Google Scholar
  10. Covington, M. A. (1994b). Natural language processing for Prolog programmers. Upper Saddle River: Prentice Hall.zbMATHGoogle Scholar
  11. Earley, J. C. (1970). An efficient context-free parsing algorithm. Communications of the ACM, 13(2), 94–102.CrossRefzbMATHGoogle Scholar
  12. Gal, A., Lapalme, G., & Saint-Dizier, P. (1989). Prolog pour l’analyse automatique du langage naturel. Paris: Eyrolles.Google Scholar
  13. Gazdar, G., & Mellish, C. (1989). Natural language processing in Prolog: An introduction to computational linguistics. Wokingham: Addison-Wesley.Google Scholar
  14. Graham, S. L., Harrison, M. A., & Ruzzo, W. L. (1980). An improved context-free recognizer. ACM Transactions on Programming Languages and Systems, 2(3), 415–462.CrossRefzbMATHGoogle Scholar
  15. Hindle, D., & Rooth, M. (1993). Structural ambiguity and lexical relations. Computational Linguistics, 19(1), 103–120.Google Scholar
  16. Johnson, M. (1998). PCFG models of linguistic tree representation. Computational Linguistics, 24(4), 613–632.Google Scholar
  17. Jurafsky, D., & Martin, J. H. (2008). Speech and language processing, an introduction to natural language processing, computational linguistics, and speech recognition (2nd ed.). Upper Saddle River: Pearson Education.Google Scholar
  18. Kasami, T. (1965). An efficient recognition and syntax analysis algorithm for context-free languages. Technical report AFCRL-65-758, Air Force Cambridge Research Laboratory, Bedford, MA. Cited from Wikipedia. Retrieved December 26, 2013.Google Scholar
  19. Klein, D., & Manning, C. D. (2003). Accurate unlexicalized parsing. In Proceedings of the 41st meeting of the association for computational linguistics, Sapporo (pp. 423–430).Google Scholar
  20. Manning, C. D., & Schütze, H. (1999). Foundations of statistical natural language processing. Cambridge, MA: MIT.zbMATHGoogle Scholar
  21. Pereira, F. C. N., & Shieber, S. M. (1987). Prolog and natural-language analysis (CSLI lecture notes, Vol. 10). Stanford: Center for the Study of Language and Information.Google Scholar
  22. Zelle, J. M., & Mooney, R. J. (1997). An inductive logic programming method for corpus-based parser construction. Technical note, University of Texas at Austin.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Pierre M. Nugues
    • 1
  1. 1.Department of Computer ScienceLund UniversityLundSweden

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