Advertisement

Parsing with Partially Known Grammar

  • Ife Adebara
  • Veronica DahlEmail author
  • Sergio Tessaris
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9494)

Abstract

We address the problem of making syntactic sense of text for which the grammar has only partial information. Our proposed methodology is to adapt a recent formalism, Womb Grammars, into parsing creative text that departs from the grammar at hand, or which cannot rely on a complete grammar being available. We argue that unspecified information can be detected with appropriate ontologies together with our adaptation of a recently introduced constraint-based methodology for acquiring linguistic information on a given language from that of another. Our implementation tool is CHRG (Constraint Handling Rule Grammars). We examine as well possible extensions to multilingual text parsing. Our proposed methodology exploits the descriptive power of constraints both for defining sentence acceptability and for inferring lexical knowledge from a word’s sentential context, even when foreign.

Keywords

Partial grammars Womb grammars Ontologies Imperfect querying Mixed language text Constraint acquisition Universal grammar Parsing CHRG (Constraint Handling Rule Grammars) Constraint based grammars Property grammars 

References

  1. 1.
    Becerra-Bonache, L., Dahl, V., Jiménez-López, M.D.: Womb grammars as a bio-inspired model for grammar induction. In: Bajo Perez, J., Corchado Rodríguez, J.M., Mathieu, P., Campbell, A., Ortega, A., Adam, E., Navarro, E.M., Arndt, S., Moreno, M.N., Soto, S.V., Julián, V. (eds.) Trends in Practical Applications of Heterogeneous Multi-agent Systems. The PAAMS Collection. AISC, vol. 293, pp. 79–86. Springer International Publishing, Heidelberg (2014) CrossRefGoogle Scholar
  2. 2.
    Becerra Bonache, L., Dahl, V., Miralles, J.E.: On second language tutoring through womb grammars. In: Rojas, I., Joya, G., Gabestany, J. (eds.) IWANN 2013, Part I. LNCS, vol. 7902, pp. 189–197. Springer, Heidelberg (2013). http://dx.doi.org/10.1007/978-3-642-38679-4_18 CrossRefGoogle Scholar
  3. 3.
    Blache, P.: Property grammars: a fully constraint-based theory. In: Christiansen, H., Skadhauge, P.R., Villadsen, J. (eds.) CSLP 2005. LNCS (LNAI), vol. 3438, pp. 1–16. Springer, Heidelberg (2005) CrossRefGoogle Scholar
  4. 4.
    Blache, P., Guénot, M.L., Vanrullen, T.: A corpus-based technique for grammar development. In: ICCL, pp. 123–131 (2003). https://halv3-preprod.archives-ouvertes.fr/hal-00135437
  5. 5.
    Burkett, D., Klein, D.: Two languages are better than one (for syntactic parsing). In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 877–886. Association for Computational Linguistics (2008)Google Scholar
  6. 6.
    Christiansen, H.: CHR grammars. TPLP 5(4–5), 467–501 (2005)MathSciNetzbMATHGoogle Scholar
  7. 7.
    Christiansen, H.: Adaptable grammars for non-context-free languages. In: Bio-Inspired Models for Natural and Formal Languages, pp. 33–51. Cambridge Scholars Publishing (2011)Google Scholar
  8. 8.
    Clark, M., Kim, Y., Kruschwitz, U., Song, D., Albakour, D., Dignum, S., Beresi, U.C., Fasli, M., De Roeck, A.: Automatically structuring domain knowledge from text: an overview of current research. Inf. Process. Manag. 48(3), 552–568 (2012)CrossRefGoogle Scholar
  9. 9.
    Cohen, S.B., Smith, N.A.: Covariance in unsupervised learning of probabilistic grammars. J. Mach. Learn. Res. 11, 3017–3051 (2010)MathSciNetzbMATHGoogle Scholar
  10. 10.
    Dahl, V., Miralles, J.: Womb grammars: constraint solving for grammar induction. In: Sneyers, J., Frühwirth, T. (eds.) Proceedings of the 9th Workshop on Constraint Handling Rules. vol. Technical report CW 624, Department of Computer Science, K.U. Leuven, pp. 32–40 (2012)Google Scholar
  11. 11.
    Dahl, V., Blache, P.: Directly executable constraint based grammars. In: Proceedings of the Journees Francophones de Programmation en Logique avec Contraintes, JFPLC 2004 (2004)Google Scholar
  12. 12.
    Dahl, V., Miralles, E., Becerra, L.: On language acquisition through womb grammars. In: 7th International Workshop on Constraint Solving and Language Processing, pp. 99–105 (2012)Google Scholar
  13. 13.
    Hovy, E., Kozareva, Z., Riloff, E.: Toward completeness in concept extraction and classification. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, vol. 2, pp. 948–957. Association for Computational Linguistics (2009)Google Scholar
  14. 14.
    Huang, C., Calzolari, N., Gangemi, A.: Ontology and the Lexicon: A Natural Language Processing Perspective. Studies in Natural Language Processing. Cambridge University Press, Cambridge (2010) CrossRefGoogle Scholar
  15. 15.
    Jackson, Q.T.: Adapting to Babel: Adaptivity and Context-Sensitivity in Parsing. Verlag: Ibis Publishing, Plymouth (2006) Google Scholar
  16. 16.
    Nicolas, L., Molinero, M.A., Sagot, B., Sánchez Trigo, E., De La Clergerie, É., Alonso Pardo, M., Farré, J., Miquel-Vergès, J.: Towards efficient production of linguistic resources: the Victoria Project. In: Proceedings of the International Conference RANLP-2009, pp. 318–323. Association for Computational Linguistics, Borovets (2009). https://hal.inria.fr/inria-00553259
  17. 17.
    Pereira, F.C., Warren, D.H.: Definite clause grammars for language analysis—a survey of the formalism and a comparison with augmented transition networks. Artif. Intell. 13(3), 231–278 (1980)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    van Rullen, T.: Vers une analyse syntaxique a granularite variable. Ph.D. thesis, Université de Provence (2005) (2005)Google Scholar
  19. 19.
    Schrijvers, T., Sulzmann, M.: Transactions in constraint handling rules. In: Garcia de la Banda, M., Pontelli, E. (eds.) ICLP 2008. LNCS, vol. 5366, pp. 516–530. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  20. 20.
    Snow, R., Jurafsky, D., Ng, A.Y.: Learning syntactic patterns for automatic hypernym discovery. In: Advances in Neural Information Processing Systems, vol. 17 (2004)Google Scholar
  21. 21.
    Snow, R., Jurafsky, D., Ng, A.Y.: Semantic taxonomy induction from heterogenous evidence. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics, pp. 801–808. ACL-44, Association for Computational Linguistics, Stroudsburg (2006). http://dx.doi.org/10.3115/1220175.1220276
  22. 22.
    Vossen, P.: EuroWordNet: a multilingual database of autonomous and language-specific wordnets connected via an inter-lingualindex. Int. J. Lexicography 17(2), 161–173 (2004). http://dx.doi.org/10.1093/ijl/17.2.161 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer ScienceSimon Fraser UniversityBurnabyCanada
  2. 2.Faculty of Computer ScienceFree University of Bozen-BolzanoBolzanoItaly
  3. 3.Institute of Software Engineering and Compiler ConstructionUniversity of UlmUlmGermany

Personalised recommendations