Skip to main content
SpringerLink
Log in

Unsupervised Coreference Resolution Using a Graph Labeling Approach

  • Conference paper
  • First Online:
Human Language Technology Challenges for Computer Science and Linguistics (LTC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8387))

Included in the following conference series:

  • 855 Accesses

Abstract

In this paper, we present a new unsupervised coreference resolution method, that models coreference resolution as a graph labeling problem. The proposed approach uses an incremental graph development method that hierarchically deploys coreference features from higher precision to lower ones. Then, a relaxation labeling method is used for solving the graph labeling problem.

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

Access this chapter

Log in via an institution
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 EPUB and 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

Institutional subscriptions

References

  1. McCallum, A., Wellner, B.: Toward conditional models of identity uncertainty with application to proper noun coreference. In: Proceedings of the IJCAI-03 Workshop on Information Integration on the Web, Acapulco, Mexico, 9–10 August 2003, pp. 79–86 (2003)

    Google Scholar 

  2. Lang, J., Qin, B., Liu, T., Li, S.: Unsupervised coreference resolution with hypergraph partitioning. Comput. Inf. Sci. 2, 55–63 (2009)

    Google Scholar 

  3. Cai, J., Mújdricza-Maydt, É., Strube, M.: Unrestricted coreference resolution via global hypergraph partitioning. In: Proceedings of the Shared Task of the 15th Conference on Computational Natural Language Learning, Portland, Oregon, 23–24 June 2011, pp. 56–60 (2011)

    Google Scholar 

  4. Sapena, E., Padró, L., Turmo, J.: RelaxCor participation in CoNLL shared task on coreference resolution. In: Proceedings of the Shared Task of the 15th Conference on Computational Natural Language Learning, Portland, Oregon, 23–24 June 2011, pp. 35–39 (2011)

    Google Scholar 

  5. Martschat, S., Cai, J., Broscheit, S., Mújdricza-Maydt, É., Strube, M.: A multigraph model for coreference resolution. In: Proceedings of the Shared Task of the 16th Conference on Computational Natural Language Learning, Jeju Island, Korea, 12–14 July 2012, pp. 100–106 (2012)

    Google Scholar 

  6. Lee, H., Chang, A., Peirsman, Y., Chambers, N., Surdeanu, M., Jurafsky, D.: Deterministic coreference resolution based on entity-centric, precision-ranked rules. Computat. Linguist. 39, 885–916 (2013)

    Article  Google Scholar 

  7. Ng, V.: Supervised noun phrase coreference research: the first fifteen years. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, Uppsala, Sweden, 11–16 July 2010, pp. 1396–1411 (2010)

    Google Scholar 

  8. 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 

  9. Yang, X., Zhou, G., Su, J., Tan, C.L.: Coreference resolution using competition learning approach. In: Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics, Sapporo, Japan, 7–12 July 2003, pp. 176–183 (2003)

    Google Scholar 

  10. Ji, H., Westbrook, D., Grishman, R.: Using semantic relations to refine coreference decisions. In: Proceedings of the Human Language Technology Conference and the 2005 Conference on Empirical Methods in Natural Language Processing, Vancouver, B.C., Canada, 6–8 October 2005 pp. 17–24 (2005)

    Google Scholar 

  11. Ponzetto, S.P., Strube, M.: Semantic role labeling for coreference resolution. In: Companion Volume to the Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics, Trento, Italy, 3–7 April 2006, pp. 143–146 (2006)

    Google Scholar 

  12. Denis, P., Baldridge, J.: Specialized models and ranking for coreference resolution. In: Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, Waikiki, Honolulu, Hawaii, 25–27 October 2008, pp. 660–669 (2008)

    Google Scholar 

  13. Bengtson, E., Roth, D.: Understanding the value of features for coreference resolution. In: Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, Waikiki, Honolulu, Hawaii, 25–27 October 2008, pp. 294–303 (2008)

    Google Scholar 

  14. Haghighi, A., Klein, D.: Simple coreference resolution with rich syntactic and semantic features. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, Singapore, 6–7 August 2009, pp. 1152–1161 (2009)

    Google Scholar 

  15. Haghighi, A., Klein, D.: Coreference resolution in a modular, entity centered model. In: Proceedings of Human Language Technologies 2010: The Conference of the North American Chapter of the Association for Computational Linguistics, Los Angeles, Cal., 2–4 June 2010, pp. 385–393 (2010)

    Google Scholar 

  16. Martschat, S.: Multigraph clustering for unsupervised coreference resolution. In: Proceedings of the Student Research Workshop at the 51st Annual Meeting of the Association for Computational Linguistics, Sofia, Bulgaria, 5–7 August 2013 (2013, to appear)

    Google Scholar 

  17. Sapena, E., Padró, L., Turmo, J.: A global relaxation labeling approach to coreference resolution. In: Proceedings of Coling 2010: Poster Volume, Beijing, China, 23–27 August 2010, pp. 1086–1094 (2010)

    Google Scholar 

  18. Raghunathan, K., Lee, H., Rangarajan, S., Chambers, N., Surdeanu, M., Jurafsky, D., Manning, C.: A multi-pass sieve for coreference resolution. In: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, Cambridge, Massachusetts, 9–11 October 2010, pp. 492–501 (2010)

    Google Scholar 

  19. Pelkowitz, L.: A continuous relaxation labeling algorithm for markov random fields. IEEE Trans. Syst. Man Cybern. 20, 709–715 (1990)

    Article  MATH  Google Scholar 

  20. Hummel, R., Zucker, S.W.: On the foundations of relaxation labeling processes. IEEE Trans. Pattern Anal. Mach. Intell. 5, 267–287 (1983)

    Article  MATH  Google Scholar 

  21. Marquez, L., Padro, L.: A flexible pos tagger using an automatically acquired language model. In: Proceedings of the Eighth Conference on European Chapter of the Association for Computational Linguistics, pp. 238–245 (1997)

    Google Scholar 

  22. Voutilainen, A., Padro, L.: Developing a hybrid NP parser. In: Proceedings of the Fifth Conference on Applied Natural Language Processing, pp. 80–87 (1997)

    Google Scholar 

  23. Cardie, C., Wagstaff, K.: Noun phrase coreference as clustering. In: Proceedings of the 1999 SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, College Park, Maryland, 21–22 June 1999, pp. 82–89 (1999)

    Google Scholar 

  24. Culotta, A., Wick, M., McCallum, A.: First-order probabilistic models for coreference resolution. In: Proceedings of Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics, Rochester, New York, 22–27 April 2007, pp. 81–88 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Sharif University of Technology, Tehran, Iran

    Nafise Sadat Moosavi & GholamReza GhassemSani

Authors
  1. Nafise Sadat Moosavi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. GholamReza GhassemSani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nafise Sadat Moosavi .

Editor information

Editors and Affiliations

  1. Adam Mickiewicz University, Poznań, Poland

    Zygmunt Vetulani

  2. IMMI-CNRS, Orsay, France

    Joseph Mariani

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Moosavi, N.S., GhassemSani, G. (2014). Unsupervised Coreference Resolution Using a Graph Labeling Approach. In: Vetulani, Z., Mariani, J. (eds) Human Language Technology Challenges for Computer Science and Linguistics. LTC 2011. Lecture Notes in Computer Science(), vol 8387. Springer, Cham. https://doi.org/10.1007/978-3-319-08958-4_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08958-4_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08957-7

  • Online ISBN: 978-3-319-08958-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation