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Multiword Units in Machine Translation and Translation Technology
Edited by Ruslan Mitkov, Johanna Monti, Gloria Corpas Pastor and Violeta Seretan
[Current Issues in Linguistic Theory 341] 2018
► pp. 243–256

Anaphora resolution, collocations and translation

Collocation identification and anaphora resolution are widely recognised as major issues for natural language processing, and particularly for machine translation. This paper focuses on their intersection domain, that is verb-object collocations in which the object has been pronominalised. To handle such cases, an anaphora resolution procedure must link the direct object pronoun to its antecedent. The identification of a collocation can then be made on the basis of the verb and its object or its antecedent. Results obtained from the translation of a large corpus will be discussed, as well as an evaluation of the precision of the anaphora resolution procedure for this specific task.

Keywords: Collocations, anaphora resolution, translation, pronominalized collocations, syntax based translation, syntax based collocation detection
Article outline
  • 1.Introduction
  • 2.Collocations in Translation
  • 3.Translating collocations with Its-2
    • 3.1Anaphora resolution
  • 4.Results and evaluation
    • 4.1Two experiments
      • Experiment 1: English
      • Experiment 2: French
      • Global results of experiments
    • 4.2Evaluation of the precision of the AR procedure
      • Evaluation settings
      • Results
      • Recall
  • 5.Conclusion
  • Notes
  • References
Published online: 20 July 2018
DOI logo
https://doi.org/10.1075/cilt.341.12weh
References
Chomsky, N.
(1977) On Wh-Movement. In P. W. Culicover, T. Wasow, and A. Akmajian (Eds.), Formal Syntax, New York, Academic Press, pages 71–132.Google Scholar
(1981) Lectures on Government and Binding, Foris Publications.Google Scholar
Grosz, B., Joshi, A. and Weinstein, S.
(1995) Centering: A Framework for Modeling the Local Coherence of Discourse. In Computation Linguistics, 21:2, pages 203–225.Google Scholar
Grosz, B. and Sidner, C. L.
(1986) Attention, Intention, and the Structure of Discourse. In Computational Linguistics, 12:3, pages 175–204.Google Scholar
Jackendoff, R.
(1997) The Architecture of the Language Faculty, Cambridge, Mass., MIT Press.Google Scholar
Kibble, R.
(2001) A Reformulation of Rule 2 of Centering Theory. In Computational Linguistics, 27:4, Cambridge, Mass., MIT Press. DOI logoGoogle Scholar
Lappin, Sh. and Leass, H.
(1994) An Algorithm for Pronominal Anaphora Resolution. In Computational Linguistics 20:4, pages 535–561.Google Scholar
Laurent, D.
(2001) De la résolution des anaphores, Rapport interne, Synapse Développement.Google Scholar
Mel’cuk, I.
(2003) Collocations : définition, rôle et utilité. In F. Grossmann, and A. Tutin (Eds.), Les collocations : analyse et traitement, Amsterdam, De Werelt, pages 23–32.Google Scholar
Mitkov, R.
(2002) Anaphora Resolution, Longman.Google Scholar
Nerima, L. and Wehrli, E.
(2013) Résolution d’anaphores appliquée aux collocations: une évaluation préliminaire. In Proceedings of TALN 2013 Conference, Les Sables d’Olonne, France.Google Scholar
Reinhart, T.
(1983) Coreference and Bound Anaphora: A Restatemt of the Anaphora Questions. In Linguistics and Philosophy, vol 6, pages 47–88. DOI logoGoogle Scholar
Russo, L., Scherrer, Y., Goldman, J.-Ph., Loaiciga, S., Nerima, L. and Wehrli, E
(2011) Etudes inter-langues de la distribution et des ambiguités syntaxiques des pronoms. In Proceedings of TALN 2011 Conference, Montpellier, France.Google Scholar
Sag, I., Baldwin, T., Bond, F., Copestake, A. and Flickinger, D.
(2002) Multiword Expressions: A Pain in the Neck for NLP. In Proceedings of Computational Linguistics and Intelligent Text Processing (CICLing-2002), Lecture Notes in Computer Science, 2276, pages 1–15.
Seretan, V.
(2011) Syntax-Based Collocation Extraction, Springer Verlag. DOI logoGoogle Scholar
Seretan, V., & Wehrli, E.
(2011, June) Fipscoview: On-line visualisation of collocations extracted from multilingual parallel corpora. In Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World (pp. 125–127).Association for Computational Linguistics.Google Scholar
Tutin, A
(2002) A Corpus-based Study of Pronominal Anaphoric Expressions in French. In Proceedings of DAARC 2002, Lisbonne, Portugal.Google Scholar
Wehrli, E.
(2007) Fips, a Deep Linguistic Multilingual Parser. In Proceedings of the ACL 2007 Workshop on Deep Linguistic processing, pages 120–127, Prague, Czech Republic.Google Scholar
Wehrli, E., Nerima, L. and Scherrer, Y.
(2009a) Deep Linguistic Multilingual Translation and Bilingual Dictionaries. In Proceedings of the Fourth Workshop on Statistical Machine Translation, pages 90–94, Athens, Greece.DOI logoGoogle Scholar
Wehrli, E., Seretan, V., Nerima, L. and Russo, R
(2009b) Collocations in a Rule-based MT System: A Case Study Evaluation of their Translation Adequacy. In Proceedings of the 13th Annual Meeting of the European Association for Machine Translation, pages 128–135, Barcelona, Spain.Google Scholar
Wehrli, E., Seretan, V. and Nerima, L.
(2010) Sentence Analysis and Collocation Identification. In Proceedings of the Workshop on Multiword Expressions: from Theory to Applications (MWE 2010), pages 27–35, Beijing, China.Google Scholar
Wehrli, E. and Nerima, L.
(2015) The Fips Multilingual Parser. In N. Gala, R. Rapp, and G. Bel-Enguix (Eds.), Language Production, Cognition and The Lexicon, Text, Speech and Language Technology (Volume 48), Springer Verlag, pages 473–490. DOI logoGoogle Scholar
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