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Mexican International Conference on Artificial Intelligence

MICAI 2011: Advances in Artificial Intelligence pp 244–257Cite as

A New General Grammar Formalism for Parsing

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7094))

Abstract

We introduce Probabilistic Constrained W-grammars (PCW-grammars), a two-level formalism capable of capturing grammatical frameworks used in three different state of the art grammar formalism, namely Bilexical Grammars, Markov Rules, and Stochastic Tree Substitution Grammars. For each of them we provide an embedding into PCW-grammars, which allows us to derive properties about their expressive power and consistency, and relations between the formalisms studied.

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References

  1. Blunsom, P., Cohn, T.: Unsupervised induction of tree substitution grammars for dependency parsing. In: Proceedings of EMNLP 2010 (2010)

    Google Scholar 

  2. Bod, R.: Enriching linguistics with statistics. Ph.D. thesis, Univ. Amsterdam (1995)

    Google Scholar 

  3. Bod, R.: Beyond Grammar—An Experience-Based Theory of Language. Cambridge University Press (1999)

    Google Scholar 

  4. Chi, Z., Geman, S.: Estimation of probabilistic context-free grammars. Compu. Ling. 305, 24:299–24:305 (1998)

    Google Scholar 

  5. Collins, M.: Three generative, lexicalized models for statistical parsing. In: ACL 1997 (1997)

    Google Scholar 

  6. Collins, M.: Head-driven statistical models for natural language parsing. Ph.D. thesis, Univ. Pennsylvania (1999)

    Google Scholar 

  7. Domníguez, M.A., Infante-Lopez, G.: Searching for Part of Speech Tags That Improve Parsing Models. In: Nordström, B., Ranta, A. (eds.) GoTAL 2008. LNCS (LNAI), vol. 5221, pp. 126–137. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  8. Eisner, J.: Three new probabilistic models for dependency parsing: An exploration. In: Proceedings of International Conference on Computational Linguistics (COLING-1996), Copenhagen (1996)

    Google Scholar 

  9. Eisner, J.: Bilexical grammars and their cubic-time parsing algorithms. In: Advances in Probabilistic and Other Parsing Technologies, pp. 29–62 (2000)

    Google Scholar 

  10. Infante-Lopez, G., de Rijke, M.: Comparing the ambiguity reduction abilities of probabilistic context-free grammars. In: Proc. LREC 2004 (2004)

    Google Scholar 

  11. Joan-Andreu, S., Bened, J.M.: Consistency of stochastic context-free grammars from probabilistic estimation based on growth transformations. IEEE Trans. on Pattern Analysis and Machine Intelligence (1997)

    Google Scholar 

  12. Johnson, M.: The dop estimation method is biased and inconsistent. Comp. Ling 76, 28:71–28:76 (2002)

    Google Scholar 

  13. Jurafsky, D., Martin, J.: Speech and Language Processing. Prentice Hall (2000)

    Google Scholar 

  14. Klein, D., Manning, C.: Corpus-based induction of syntactic structure: Models of dependency and constituency. In: Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics (2004)

    Google Scholar 

  15. Koo, T., Carreras, X., Collins, M.: Simple semi-supervised dependency parsing. In: Proc. ACL/HLT (2008)

    Google Scholar 

  16. Manning, C., Schütze, H.: Foundations of Statistical Natural Language Processing. The MIT Press (1999)

    Google Scholar 

  17. Sima’an, K., Buratto, L.: Backoff Parameter Estimation for the DOP Model. In: Lavrač, N., Gamberger, D., Todorovski, L., Blockeel, H. (eds.) ECML 2003. LNCS (LNAI), vol. 2837, pp. 373–384. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  18. Spitkovsky, V.I., Alshawi, H., Jurafsky, D., Manning, C.D.: Viterbi training improves unsupervised dependency parsing. In: Proc. CoNLL 2010 (2010)

    Google Scholar 

  19. van Wijngaarden, A.: Orthogonal design and description of a formal language. In: Technical Report MR76, Mathematisch Centrum, Amsterdam (1965)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Grupo de Procesamiento de Lenguaje Natural, Universidad Nacional de Córdoba, Argentina

    Gabriel Infante-Lopez & Martín Ariel Domínguez

Authors
  1. Gabriel Infante-Lopez
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  2. Martín Ariel Domínguez
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Editor information

Editors and Affiliations

  1. Mexican Petroleum Institute (IMP), Eje Central Lazaro Cardenas Norte, 152, Col. San Bartolo Atepehuacan, CP 07730,, Mexico DF,, Mexico

    Ildar Batyrshin

  2. National Polytechnic Institute (IPN), Center for Computing Research (CIC), Av. Juan Dios Bátiz, s/n, Col. Nueva Industrial Vallejo, CP 07738, Mexico D.F., Mexico

    Grigori Sidorov

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© 2011 Springer-Verlag Berlin Heidelberg

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Infante-Lopez, G., Domínguez, M.A. (2011). A New General Grammar Formalism for Parsing. In: Batyrshin, I., Sidorov, G. (eds) Advances in Artificial Intelligence. MICAI 2011. Lecture Notes in Computer Science(), vol 7094. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25324-9_21

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  • DOI: https://doi.org/10.1007/978-3-642-25324-9_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25323-2

  • Online ISBN: 978-3-642-25324-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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