Utility for Communicability by Profit and Cost of Agreement

  • Ryuichi Matoba
  • Makoto Nakamura
  • Satoshi Tojo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4211)


The inflection of words based on agreement, such as number, gender and case, is considered to contribute to clarify the dependency between words in a sentence. Our purpose in this study is to investigate the efficiency of word inflections with HPSG (Head–driven Phrase Structure Grammar), which is able to deal with these features directly. Using a notion of utility, we measure the efficiency of a grammar in terms of the balance between the number of semantic structures of a sentence, and the cost of agreement according to the number of unification processes. In our experiments, we showed how these were balanced in two different corpora. One, WSJ (Wall Street Journal), includes long and complicated sentences, while the other corpus, ATIS (Air Travel Information System) does shorter colloquial sentences. In the both corpora, agreement is surely important to reduce ambiguity. However, the importance of agreement in the ATIS corpus became salient as personal pronouns were so often employed in it, compared with the WSJ corpus.


Relative Clause Word Order Wall Street Journal Mixture Ratio Personal Pronoun 
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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  1. 1.
    Anward, J.: Word Classes / Parts of Speech: Overview. In: Brown, K. (ed.) The Encyclopedia of Language and Linguistics, 2nd edn., vol. 13, pp. 628–629. Elsevier Science Publishers, Amsterdam (2006)Google Scholar
  2. 2.
    Barlow, M., Ferguson, C.A. (eds.): Agreement in Natural Language: Approaches, Theories, Descriptions. CSLI, Stanford (1988)Google Scholar
  3. 3.
    Blake, B.J.: Case. Cambridge University Press, Cambridge (1994)Google Scholar
  4. 4.
    Briscoe, T.: Grammatical acquisition and linguistic selection. In: Linguistic Evolution through Language Acquisition, Cambridge University Press, Cambridge (2002)CrossRefGoogle Scholar
  5. 5.
    Gunji, T.: Japanese Phrase Structure Grammar. Reidel, Dordrecht (1987)Google Scholar
  6. 6.
    Jackendoff, R.: Foundations of Language: Brain, Meaning, Grammar, Evolution. Oxford University Press, Oxford (2002)Google Scholar
  7. 7.
    Jäger, G.: Evolutionary Game Theory and Typology: a Case Study. In: Proceedings of the 14th Amsterdam Colloquium, pp. 108–117 (2003)Google Scholar
  8. 8.
    Kirby, S.: Learning, Bottlenecks and the Evolution of Recursive Syntax. In: Linguistic Evolution through Language Acquisition. Cambridge University Press, Cambridge (2002)Google Scholar
  9. 9.
    Makino, T., Torisawa, K., Tsujii, J.: Lilfes–Pactical Programming Language For Typed Feature Structures. In: Natural Language Pacific Rim Symposium (1997)Google Scholar
  10. 10.
    Miyao, Y., Tsujii, J.: Probabilistic Disambiguation Models for Wide–Coverage HPSG parsing. In: ACL 2005 (2005)Google Scholar
  11. 11.
    Sag, I., Wasow, T., Bender, E.: Syntactic Theory - A Formal Introduction, 2nd edn. CSLI Publications (2003)Google Scholar
  12. 12.
    Steels, L., Beule, J.D.: A (very) Brief Introduction to Fluid Construction Grammar. In: Proceedings of the 3rd International Workshop on Scalable Natural Language (ScaNaLu 2006) (to appear, 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ryuichi Matoba
    • 1
  • Makoto Nakamura
    • 1
  • Satoshi Tojo
    • 1
  1. 1.School of Information Science, Japan Advanced Institute of Science and TechnologyNomi, IshikawaJapan

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