Unsupervised Learning of P NP P Word Combinations

  • Sofía N. Galicia-Haro
  • Alexander Gelbukh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3406)

Abstract

We evaluate the possibility to learn, in an unsupervised manner, a list of idiomatic word combinations of the type preposition + noun phrase + preposition (P NP P), namely, such groups with three or more simple forms that behave as a whole lexical unit and have semantic and syntactic properties not deducible from the corresponding properties of each simple form, e.g., by means of, in order to, in front of. We show that idiomatic P NP P combinations have some statistical properties distinct from those of usual idiomatic collocations. In particular, we found that most frequent P NP P trigrams tend to be idiomatic. Of other statistical measures, log-likelihood performs almost as good as frequency for detecting idiomatic expressions of this type, while chi-square and point-wise mutual information perform very poor. We experiment on Spanish material.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Banerjee, S., Pedersen, T.: The Design, Implementation, and Use of the Ngram Statistics Package. In: Gelbukh, A. (ed.) CICLing 2003. LNCS, vol. 2588. Springer, Heidelberg (2003), http://www.d.umn.edu/~tpederse/nsp.html CrossRefGoogle Scholar
  2. 2.
    Degand, L., Bestgen, Y.: Towards automatic retrieval of idioms in French newspaper corpora. Literary and Linguistic Computing 18(3), 249–259 (2003)CrossRefGoogle Scholar
  3. 3.
    Evert, S., Krenn, B.: Methods for the Qualitative Evaluation of Lexical Association. In: Proc. ACL 2001, pp. 188–195 (2001)Google Scholar
  4. 4.
    Galicia-Haro, S.N.: Using Electronic Texts for an Annotated Corpus Building. In: 4th Mexican International Conference on Computer Science, ENC 2003, Mexico, pp. 26–33 (2003)Google Scholar
  5. 5.
    Justeson, J.S., Katz, S.M.: Technical Terminology: Some Linguistic properties and an algorithm for identification in text. Natural Language Engineering 1, 9–27 (1995)CrossRefGoogle Scholar
  6. 6.
    Manning, C.D., Schutze, H.: Foundations of Statistical Natural Language Processing. The MIT Press, Cambridge (1999)MATHGoogle Scholar
  7. 7.
    Nañez Fernández, E.: Diccionario de construcciones sintácticas del español. Preposiciones. Editorial de la Universidad Autónoma de Madrid (1995)Google Scholar
  8. 8.
    Rayson, P., Berridge, D., Francis, B.: Extending the Cochran rule for the comparison of word frequencies between corpora. In: Purnelle, G., et al. (eds.) Le poids des mots: Proc. of 7th International Conf. on Statistical analysis of textual data, JADT 2004 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sofía N. Galicia-Haro
    • 1
  • Alexander Gelbukh
    • 2
  1. 1.Faculty of SciencesUNAM Universitary CityMexico CityMexico
  2. 2.Center for Computing ResearchNational Polytechnic InstituteMexico

Personalised recommendations