Skip to main content

Selection Restrictions Acquisition from Corpora

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2258))

Abstract

This paper describes an automatic clustering strategy for acquiring selection restrictions. We use a knowledge-poor method merely based on word cooccurrence within basic syntactic constructions; hence, neither semantic tagged corpora nor man-made lexical resources are needed for generalising semantic restrictions. Our strategy relies on two basic linguistic assumptions. First, we assume that two syntactically related words impose semantic selectional restrictions to each other (cospecification). Second, it is also claimed that two syntactic contexts impose the same selection restrictions if they cooccur with the same words (contextual hypothesis). In order to test our learning method, preliminary experiments have been performed on a Portuguese corpus.

Research supported by the PRAXIS XXI project, FCT/MCT, Portugal

Research sponsored by CAPES and PUCRS - Brazil

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Roberto Basili, Maria Pazienza, and Paola Velardi. Hierarchical clustering of verbs. In Workshop on Acquisition of Lexical Knowledge from Text, pages 56–70, Ohio State University, USA, 1993.

    Google Scholar 

  2. Gilles Bisson, Claire Nédellec, and Dolores Canamero. Designing clustering methods for ontology building: The mo’k workbench. In Internal rapport, http://citerseer.nj.nec.com/316335.html, 2000.

  3. Ido Dagan, Lillian Lee, and Fernando Pereira. Similarity-based methods of word coocurrence probabilities. Machine Learning, 43, 1998.

    Google Scholar 

  4. David Faure and Claire Nédellec. Asium: Learning subcategorization frames and restrictions of selection. In ECML98, Workshop on Text Mining, 1998.

    Google Scholar 

  5. David Faure. Conception de méthode d’aprentissage symbolique et automatique pour l’acquisition de cadres de sous-catégorisation de verbes et de connaissances sémantiques à partir de textes: le système ASIUM. PhD thesis, Université Paris XI Orsay, Paris, France, 2000.

    Google Scholar 

  6. Francesc Ribas Framis. On learning more appropriate selectional restrictions. In Proceedings of the 7th Conference of the European Chapter of the Association for Computational Linguistics, Dublin, 1995.

    Google Scholar 

  7. Pablo Gamallo, Caroline Gasperin, Alexandre Agustini, and Gabriel P. Lopes. Syntactic-based methods for measuring word similarity. In Text, Speech, and Discourse (TSD-2001). Berlin: Springer Verlag (to appear), 2001.

    Google Scholar 

  8. Pablo Gamallo. Construction conceptuelle d’expressions complexes: traitement de la combinaison nom-adjectif. PhD thesis, Université Blaise Pascal, Clermont-Ferrand, France, 1998.

    Google Scholar 

  9. Gregory Grefenstette. Explorations in Automatic Thesaurus Discovery. Kluwer Academic Publishers, USA, 1994.

    MATH  Google Scholar 

  10. Gregory Grefenstette. Evaluation techniques for automatic semantic extraction: Comparing syntatic and window based approaches. In Branimir Boguraev and James Pustejovsky, editors, Corpus processing for Lexical Acquisition, pages 205–216. The MIT Press, 1995.

    Google Scholar 

  11. Ralph Grishman and John Sterling. Generalizing automatically generated selectional patterns. In Proceedings of the 15th International on Computational Linguistics (COLING-94), 1994.

    Google Scholar 

  12. D. Hindle. Noun classification form predicate-argument structures. In Proceedings of the 28th Meeting of the ACL, pages 268–275, 1990.

    Google Scholar 

  13. Dekang Lin. Automatic retrieval and clustering of similar words. In COLING-ACL’98, Montreal, 1998.

    Google Scholar 

  14. Nuno Marques. Uma Metodologia para a Modelação Estatística da Subcategorização Verbal. PhD thesis, Universidade Nova de Lisboa, Lisboa, Portugal, 2000.

    Google Scholar 

  15. Fernando Pereira, Naftali Tishby, and Lillian Lee. Distributional clustering of english words. In Proceedings of the 30th Annual Meeting of the Association of Comptutational Linguistics, pages 183–190, Columbos, Ohio, 1993.

    Google Scholar 

  16. James Pustejovsky. The Generative Lexicon. MIT Press, Cambridge, 1995.

    Google Scholar 

  17. Philip Resnik. Semantic similarity in taxonomy: An information-based measure and its application to problems of ambiguity in natural language. Journal of Artificial Intelligence Research, 11:95–130, 1999.

    MATH  Google Scholar 

  18. V. Rocio, E. de la Clergerie, and J.G.P. Lopes. Tabulation for multi-purpose partial parsing. Journal of Grammars, 4(1), 2001.

    Google Scholar 

  19. Satoshi Sekine, Jeremy Carrol, Sofia Ananiadou, and Jun'ichi Tsujii. Automatic learning for semantic collocation. In Proceedings of the 3rd Conference on Applied Natural Language Processing, pages 104–110, 1992.

    Google Scholar 

  20. Tokunaga Takenobu, Iwayama Makoto, and Tanaka Hozumi. Automatic thesaurus construction based on grammatical relations. In Proceedings of IJCAI-95, 1995.

    Google Scholar 

  21. Luis Talavera and Javier Béjar. Integrating declarative knowledge in hierarchical clustering tasks. In Intelligent Data Analysis, pages 211–222, 1999.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gamallo, P., Agustini, A., Lopes, G.P. (2001). Selection Restrictions Acquisition from Corpora. In: Brazdil, P., Jorge, A. (eds) Progress in Artificial Intelligence. EPIA 2001. Lecture Notes in Computer Science(), vol 2258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45329-6_7

Download citation

  • DOI: https://doi.org/10.1007/3-540-45329-6_7

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43030-8

  • Online ISBN: 978-3-540-45329-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics