Skip to main content

Pronoun Resolution with Markov Logic Networks

  • Conference paper
Information Retrieval Technology (AIRS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4993))

Included in the following conference series:

  • 1410 Accesses

Abstract

Pronoun resolution refers to the problem of determining the coreference linkages between the antecedents and the pronouns. We propose to employ a combined model of statistical learning and first-order logic, the Markov logic network (MLN). Our proposed model can more effectively characterize the pronoun coreference resolution process that requires conducting inference upon a variety of conditions. The influence of different types of constraints are also investigated.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Richardson, M., Domingos, P.: Markov logic networks. Machine Learning 62, 107–136 (2006)

    Article  Google Scholar 

  2. Chomsky, N.: The Minimalist Program. MIT Press, Cambridge (1995)

    MATH  Google Scholar 

  3. Harris, C., Bates, E.A.: Clausal backgrounding and pronominal reference: A functionalist approach to c-command. Language and Congitive Processes 17(3), 237–269 (2002)

    Article  Google Scholar 

  4. Hobbs, J.: Resolving pronoun references. Readings in natural language processing, 339–352 (1986)

    Google Scholar 

  5. Grosz, B.J., Weinstein, S., Joshi, A.K.: Centering: a framework for modeling the local coherence of discourse. Comput. Linguist. 21(2), 203–225 (1995)

    Google Scholar 

  6. Ge, N., Hale, J., Charniak, E.: A statistical approach to anaphora resolution. In: Proceedings of the Sixth Workshop on Very Large Corpora (1998)

    Google Scholar 

  7. Soon, W.M., Ng, H.T., Lim, D.C.Y.: A machine learning approach to coreference resolution of noun phrases. Comput. Linguist. 27(4), 521–544 (2001)

    Article  Google Scholar 

  8. Wellner, B., McCallum, A.: Towards conditional models of identity uncertainty with application to proper noun coreference. In: IJCAI Workshop on Information Integration and the Web (2003)

    Google Scholar 

  9. Cardie, C., Wagstaff, K.: Noun phrase coreference as clustering. In: Proceedings of the EMNLP and VLC (1999)

    Google Scholar 

  10. Luo, X., Zitouni, I.: Multi-lingual coreference resolution with syntactic features. In: Proceedings of Human Language Technology Coreference and Coreference on Empirical Methods in Natural Language Processing(HLT/EMNLP), Vancouver, october 2005, pp. 660–667 (2005)

    Google Scholar 

  11. Ng, V.: Shallow semantics for coreference resolution. In: Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI) (2007)

    Google Scholar 

  12. Ponzetto, S.P., Strube, M.: Exploiting semantic role labeling, wordnet and wikipedia for coreference resolution. In: Proceedings of NAACL (2006)

    Google Scholar 

  13. Lappin, S., Leass, H.: An algorithm for pronominal anaphora resolution. Computational Linguistics 20(4), 535–561 (1994)

    Google Scholar 

  14. Bergsma, S.: Boostrapping path-based pronoun resolution. In: Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the ACL, pp. 33–40 (2006)

    Google Scholar 

  15. Mitkov, R.: Robust pronoun resolution with limited knowledge. In: Proceedings of the 17th International Conference on Computational Linguistics, pp. 869–875 (1998)

    Google Scholar 

  16. Kehler, A., Appeit, D., Taylor, L., Simma, A.: The (non)utility of predicate-arguement frequencies for pronoun interpretation. In: Proceedings of 2004 North American chapter of the Association for Computational Linguistics annual meeting (2004)

    Google Scholar 

  17. Yang, X., Su, J., Tan, C.L.: Improving pronoun resolution using statistic-based semantic compatibility information. In: Proceedings of the 43rc Annual Meeting of the ACL, pp. 33–40 (2005)

    Google Scholar 

  18. Charniak, E.: A maximum-entropy-inspired parser. In: Proceedings of NAACL (2000)

    Google Scholar 

  19. Vilain, M., Burger, J., Connolly, D., Hirschman, L.: A model-theoretic coreference scoring scheme. In: Proceedings of MUC-6, pp. 176–183 (1995)

    Google Scholar 

  20. Kok, S., Domingos, P.: The alchemy system for statistical relational AI, Technical report, Department of Computer Science and Engineering, University of Washington, Seattle, WA (2005) http://www.cs.washington.edu/ai/alchemy/

  21. Harabagiu, S., Maiorano, S.: Knowledge-lean coreference resolution and its relation to textual cohesion and coherence. In: Proceedings of the ACL 1999 Workshop on the Relation of Discourse Dialogue Structure and Reference, pp. 29–38 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Hang Li Ting Liu Wei-Ying Ma Tetsuya Sakai Kam-Fai Wong Guodong Zhou

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chan, K., Lam, W. (2008). Pronoun Resolution with Markov Logic Networks. In: Li, H., Liu, T., Ma, WY., Sakai, T., Wong, KF., Zhou, G. (eds) Information Retrieval Technology. AIRS 2008. Lecture Notes in Computer Science, vol 4993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68636-1_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-68636-1_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68633-0

  • Online ISBN: 978-3-540-68636-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics