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Outstanding Issues in Anaphora Resolution

  • Ruslan Mitkov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2004)

Abstract

This paper argues that even though there has been considerable ad- vance in the research in anaphora resolution over the last 10 years, there are still a number of outstanding issues. The paper discusses several of these issues and outlines some of the work underway to address them with particular reference to the work carried out by the author’s research team.

Keywords

Noun Phrase Machine Translation Computational Linguistics Outstanding Issue Annotate Corpus 
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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References

  1. 1.
    Alshawi, H.: Resolving quasi logical forms. Computational Linguistics, 16:3 (1990)Google Scholar
  2. 2.
    Aone, C., McKee, D.: A language-independent anaphora resolution system for understanding multilingual texts. In: Proceedings of the 31st Annual Meeting of the ACL (ACL’93), (1993) 156–163Google Scholar
  3. 3.
    Aone, C., Bennett, S.: Evaluating automated and manual acquisition of anaphora resolution rules. In: Proceedings of ACL’95, (1995) 122–129Google Scholar
  4. 4.
    Azzam, S., Humphreys, K., Gaizauskas, R.: Coreference resolution in a multilingual information extraction. In: Proceedings of the Workshop on Linguistic Coreference. Granada, Spain (1998)Google Scholar
  5. 5.
    Bagga, A.: Evaluation of coreferences and coreference resolution systems. In: Proceedings of the Second Colloquium on Discourse Anaphora and Anaphor Resolution (DAARC2), Lancaster, UK (1998) 28–33Google Scholar
  6. 6.
    Baldwin, B.: CogNIAC: high precision coreference with limited knowledge and linguistic resources. In: Proceedings of the ACL’97/EACL’97 workshop on Operational factors in practical, robust anaphora resolution Madrid, Spain (1997) 38–45Google Scholar
  7. 7.
    Barbu, C., Mitkov. R.: Evaluation environment for anaphora resolution. In: Proceedings of the International Conference on Machine Translation and Multilingual Applications (MT2000), Exeter, UK. (2000) 18.1–18.8Google Scholar
  8. 8.
    Byron, D.: A proposal for consistent evaluation of pronoun resolution algorithms. (2001) (forthcoming)Google Scholar
  9. 9.
    Carbonell, J., Brown R.: Anaphora Resolution: a Multi-Strategy Approach. In: Proceedings of the 12. International Conference on Computational Linguistics (COLING’88), Vol.I, Budapest, Hungary (1988) 96–101Google Scholar
  10. 10.
    Cardie, C., Wagstaff, K: Noun phrase coreference as clustering. In: Proceedings of the 1999 Joint SIGDAT conference on Empirical Methods in NLP and Very Large Corpora (ACL’99) University of Maryland, USA. (1999) 82–Google Scholar
  11. 11.
    Carter, D.: Interpreting Anaphora in Natural Language Texts. Ellis Horwood, Chichester (1987)Google Scholar
  12. 12.
    Carter, D.: Control issues in anaphor resolution. In: Journal of Semantics, 7, (1990) 435–454CrossRefGoogle Scholar
  13. 13.
    Collins, M.: Three generative, lexicalised models for statistical parsing. In: Proceedings of the 35th Annual Meeting of the ACL (ACL’97) Madrid, Spain (1997) 16–Google Scholar
  14. 14.
    Daelemans, W., Zavarel, J., van der Slot, K., van den Bosch, A.: Timbl: Tilburg Memory Based Learner, version 2.0. Reference guide, ILK technical report ILK, Tilburg University (1999) 99–01Google Scholar
  15. 15.
    Dagan, I. and Itai, A.: Automatic processing of large corpora for the resolution of anaphora references. In: Proceedings of the 13th International Conference on Computational Linguistics (COLING’90), Vol. III, 1–3, Helsinki, Finland (1990) 1-3Google Scholar
  16. 16.
    Dagan, I., Itai, A.: A statistical filter for resolving pronoun references. In: Y.A. Feldman, Y.A, Bruckstein, A (eds): Artificial Intelligence and Computer Vision, Elsevier Science Publishers B.V. (North-Holland) (1991) 125–135Google Scholar
  17. 17.
    Denber, M.: Automatic resolution of anaphora in English. Internal Report. Eastman Kodak Co. (1988)Google Scholar
  18. 18.
    Evans, R.: A Comparison of Rule-Based and Machine Learning Methods for Identifying Non-nominal It. In: Natural Language Processing-NLP2000, Second International Conference Proceedings, Lecture Notes in Artificial Intelligence, Springer-Verlag, (2000) 233–242Google Scholar
  19. 19.
    Evans, R.: Applying machine learning toward an automatic classification of it. In: Literary and Linguistic Computing (2001) (forthcoming)Google Scholar
  20. 20.
    Evans, R, Orasan, C.: Improving anaphora resolution by identifying animate entities in texts. In: Proceedings of the Discourse, Anaphora and Reference Resolution Conference (DAARC2000). Lancaster, UK. (2000)Google Scholar
  21. 21.
    Ferrandez, A., Palomar. M., Moreno L.: Slot unification grammar and anaphora resolution. In: Proceedings of the International Conference on Recent Advances in Natural Language Proceeding (RANLP.97) Tzigov Chark, Bulgaria (1997) 294–299Google Scholar
  22. 22.
    Fukumoto, F., Yamada, H, Mitkov, R.: Resolving overt pronouns in Japanese using hierarchical VP structures. In: Proceedings of Corpora and NLP Monastir, Tunisia. (2000) 152–1Google Scholar
  23. 23.
    Ge, N., Hale, J., Charniak, E.: A statistical approach to anaphora resolution. In: Proceedings of the Workshop on Very Large Corpora. Montreal. Canada. (1998) 161–170Google Scholar
  24. 24.
    Gelbukh, A., Sidorov G.: On Indirect Anaphora Resolution. In: Proceedings of PACLING-99, Waterloo, Ontario, Canada, (1999) 181–1Google Scholar
  25. 25.
    Grishman, R.: Information extraction. In: Mitkov R., Oxford Handbook of Computational Linguistics, Oxford University Press (2001) (forthcoming)Google Scholar
  26. 26.
    Harabagiu, S., Maiorano, S. J: Multilingual Coreference Resolution. In: Proceedings of ANLP-NAACL2000 (2000) 142–149Google Scholar
  27. 27.
    Hirschman, L.: MUC-7 coreference task definition. Version 3.0 (1997)Google Scholar
  28. 28.
    Hobbs, J. R.: Pronoun resolution. Research Report 76-1. New York: Department of Computer Science, City University of New York (1976)Google Scholar
  29. 29.
    Hobbs, J. R.: Resolving pronoun references. Lingua, 44 (1978) 339–352.CrossRefGoogle Scholar
  30. 30.
    Kameyama, M.: Recognizing referential links: an information extraction perspective. In: Proceedings of the ACL’97/EACL’97 workshop on Operational factors in practical, robust anaphora resolution Madrid, Spain (1997) 46–53Google Scholar
  31. 31.
    Kennedy, C. Boguraev, B.: Anaphora for everyone: pronominal anaphora resolution without a parser. In: Proceedings of the 16th International Conference on Computational Linguistics (COLING’96)Copenhagen, Denmark (1996) 113–118Google Scholar
  32. 32.
    Lappin, S., Leass, H.: An algorithm for pronominal anaphora resolution, Computational Linguistics, 20(4), (1994) 535–561Google Scholar
  33. 33.
    Leech, G. and Garside, R.: Running a grammar factory: the production of syntactically analysed corpora or “treebanks”. In: Johannsson, S., Stenstrom, A. (eds.), English Computer Corpora: Selected Papers and Research Guide. Mouton De Gruyter, Berlin (1991) 15–32Google Scholar
  34. 34.
    Mitkov, R.: An uncertainty reasoning approach for anaphora resolution. In: Proceedings of the Natural Language Processing Pacific Rim Symposium (NLPRS’95), Seoul, Korea (1995) 149–1Google Scholar
  35. 35.
    Mitkov, R.: Pronoun resolution: the practical alternative. Paper presented at the Discourse Anaphora and Anaphor Resolution Colloquium (DAARC), Lancaster, UK (1996). Also appeared in: Botley, S., McEnery, T. (eds): Corpus-based and computational approaches to discourse anaphora. John Benjamins, Amsterdam/Philadelphia (2000)189–212Google Scholar
  36. 36.
    Mitkov, R.: Factors in anaphora resolution: they are not the only things that matter. A case study based on two different approaches. In: Proceedings of the ACL’97/EACL’97 workshop on Operational factors in practical, robust anaphora resolution, Madrid, Spain (1997) 14–Google Scholar
  37. 37.
    Mitkov, R.: Evaluating anaphora resolution approaches. In: Proceedings of the Discourse Anaphora and Anaphora Resolution Colloquium (DAARC’2). Lancaster, UK (1998)Google Scholar
  38. 38.
    Mitkov, R.: Robust pronoun resolution with limited knowledge. In: Proceedings of the 18th International Conference on Computational Linguistics (COLING’98)/ACL’98 Conference Montreal, Canada (1998) 869–875Google Scholar
  39. 39.
    Mitkov, R.: Towards more consistent and comprehensive evaluation in anaphora resolution. In: Proceedings of LREC’2000, Athens, Greece, (2000) 1309–1314Google Scholar
  40. 40.
    Mitkov, R.: Towards more consistent and comprehensive evaluation of robust anaphora resolution algorithms and systems. Invited talk. In: Proceedings of the Discourse, Anaphora and Reference Resolution Conference (DAARC2000), (forthcoming). Lancaster, UK (2000)Google Scholar
  41. 41.
    Mitkov, R.: Multilingual anaphora resolution. Machine Translation. (2000) (forthcoming)Google Scholar
  42. 42.
    Mitkov, R.: Anaphora resolution. Longman (2001) (forthcoming).Google Scholar
  43. 43.
    Mitkov, R., Stys, M.: Robust reference resolution with limited knowledge: high precision genre-specific approach for English and Polish. In: Proceedings of the International Conference “Recent Advances in Natural Language Proceeding” (RANLP’97) Tzigov Chark, Bulgaria (1997) 74–Google Scholar
  44. 44.
    Mitkov, R., Barbu, C.: Improving pronoun resolution in two languages by means of bilingual corpora. In : Proceedings of the Discourse, Anaphora and Reference Resolution Conference (DAARC 2000), Lanscaster, UK. (2000)Google Scholar
  45. 45.
    Mitkov, R., Belguith, L., Stys, M.: Multilingual robust anaphora resolution. In: Proceedings of the Third International Conference on Empirical Methods in Natural Language Processing (EMNLP-3). Granada, Spain (1998) 7–16Google Scholar
  46. 46.
    Mitkov, R., Orasan, C., and Evans, R.: The importance of annotated corpora for NLP: the cases of anaphora resolution and clause splitting. In: Proceedings of “Corpora and NLP: Reflecting on Methodology Workshop”. TALN’99, Corsica, France (1999) 60–Google Scholar
  47. 47.
    Mitkov, R., Evans, R., Orasan, C., Barbu, C., L. Jones, L., Sotirova, V.: Coreference and anaphora: developing annotating tools, annotated resources and annotation strategies. In: Proceedings of the Discourse, Anaphora and Reference Resolution Conference (DAARC2000). Lancaster, UK. (2000)Google Scholar
  48. 48.
    Munoz, R., Palomar, M.: Processing of Spanish definite description with the same head. In: Proceedings of NLP’2000, Patras, Greece (2000) 212–220Google Scholar
  49. 49.
    Munoz, R., Saiz-Noeda, M., Suárez, A., Palomar, M.: Semantic approach to bridging reference resolution. In: Proceedings of the International Conference Machine Translation and Multilingual Applications (MT2000) Exeter, UK. (2000) 17-1-17Google Scholar
  50. 50.
    Murata, M., Nagao, M.: Indirect reference in Japanese sentences. In: Botley, S., McEnery, T. (eds): Corpus-based and computational approaches to discourse anaphora. John Benjamins, Amsterdam/Philadelphia (2000) 211–226Google Scholar
  51. 51.
    Nasukawa, T.: Robust method of pronoun resolution using full-text information. In: Proceedings of the 15th International Conference on Computational Linguistics (COLING’94) Kyoto, Japan (1994) 1157–11Google Scholar
  52. 52.
    Orasan, C.: ClinkA - a coreferential links annotator. In: Proceedings of the Second International Conference on Languages Resources and Evaluation (LRE’2000), Athens, Greece (2000)Google Scholar
  53. 53.
    Orasan C., Evans R., and Mitkov R.: Enhancing Preference-Based Anaphora Resolution with Genetic Algorithms, In Proceedings of NLP’2000, Patras, Greece (2000) 185–Google Scholar
  54. 54.
    Paice, C.D., Husk, G.D.: Towards the automatic recognition of anaphoric features in English text: the impersonal pronoun ‘it’” In: Computer Speech and Language, 2, (1987) 109–132CrossRefGoogle Scholar
  55. 55.
    Poesio, M., Vieira, R., Teufel, S.: Resolving bridging references in unrestricted text. In: Proceedings of the ACL’97/EACL’97 workshop on Operational factors in practical, robust anaphora resolution, Madrid, Spain (1997) 1–Google Scholar
  56. 56.
    Preuβ S., Schmitz, B., Hauenschild, C., Umbach, U.: Anaphora Resolution in Machine Translation. Studies in Machine Translation and Natural Language Processing. In: Ramm, W.(ed): (Vol. 6 “Text and content in Machine Translation: Aspects of discourse representation and discourse processing”): Luxembourg: Office for Official Publications of the European Community (1994) 29–52Google Scholar
  57. 57.
    Rich, E., LuperFoy S.: An Architecture for Anaphora Resolution. In: Proceedings of the Second Conference on Applied Natural Language Processing (ANLP-2), Austin, Texas, U.S.A. (1988) 18–24Google Scholar
  58. 58.
    Sidner, C.: Toward a computational theory of definite anaphora comprehension in English. Technical report No. AI-TR-537. MIT Press, Cambridge, Massachussetts (1979)Google Scholar
  59. 59.
    Tanev, H., Mitkov, R.:LINGUA-a robust architecture for text processing and anaphora resolution in Bulgarian. In: Proceedings of the International Conference on Machine Translation and Multilingual Applications (MT2000), Exeter, UK. (2000) 20.1–20.Google Scholar
  60. 60.
    Tetreault, J. R.: Analysis of Syntax-Based Pronoun Resolution Methods. In: Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, Maryland, USA. (1999) 602–6Google Scholar
  61. 61.
    Tapanainen, P., T. Jarvinen, T.: A non-projective Dependency Parser. In: Proceedings of the 5th Conference of Applied Natural Language Processing, ACL, USA. (1997) 64–Google Scholar
  62. 62.
    Vieira, R., Poesio, M.: Processing definite descriptions in corpora In: Botley, S., McEnery, T. (eds): Corpus-based and computational approaches to discourse anaphora. John Benjamins, Amsterdam/Philadelphia (2000a) 189–212Google Scholar
  63. 63.
    Vieira, R., Poesio, M.: An empirically-based system for processing definite descriptions. In: Computational Linguistics (2000b) 26(4).Google Scholar
  64. 64.
    Walker, M., Joshi, A., Prince, E.: Centering in naturally occurring discourse: an overview. In: Walker, M., Joshi, A., Prince, E. (eds): Centering theory in discourse. Clarendon Press, Oxford (1998)Google Scholar
  65. 65.
    Williams, S., Harvey, M., Preston, K.: Rule-based reference resolution for unrestricted text using part-of-speech tagging and noun phrase parsing. In: Proceedings of the International Colloquium on Discourse Anaphora and Anaphora Resolution (DAARC), Lancaster, UK. (1996) 441–4Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Ruslan Mitkov
    • 1
  1. 1.School of Humanities, Languages and Social StudiesUniversity of WolverhamptonWolverhamptonUK

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