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Findings of the 2016 WMT Shared Task on Cross-lingual Pronoun Prediction

  • Liane Guillou
    ,
  • ,
  • Preslav Nakov
    ,
  • Sara Stymne
    ,
  • Jörg Tiedemann
    ,
  • Yannick Versley
  • Ludwig Maximilian University of Munich
    ,
  • Uppsala University
    ,
  • Qatar Computing Research institute
    ,
  • University of Helsinki
    ,
  • LinkedIn
    ,
  • Fondazione Bruno Kessler
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Publication milestones

  • Published - 12/08/2016

Publication status

Published - 12/08/2016
978-1-945626-10-4

Publication IDs

  • ORCID: /0000-0002-6103-7275/work/106363254
  • Scopus: 85123176898

Host publication title

Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers

Abstract

We describe the design, the evaluation setup, and the results of the 2016 WMT shared task on cross-lingual pronoun prediction. This is a classification task in which participants are asked to provide predictions on what pronoun class label should replace a placeholder value in the target-language text, provided in lemmatised and PoS-tagged form. We provided four subtasks, for the English–French and English–German language pairs, in both directions. Eleven teams participated in the shared task; nine for the English–French subtask, five for French–English,nine for English–German, and six for German–English. Most of the submissionsoutperformed two strong language-modelbased baseline systems, with systems using deep recurrent neural networks outperforming those using other architectures for most language pairs.

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