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

  • Liane Guillou
  • , Christian Hardmeier
  • , Preslav Nakov
  • , Sara Stymne
  • , Jörg Tiedemann
  • , Yannick Versley
  • , Mauro Cettolo
  • , Bonnie Webber
  • , Andrei Popescu-Belis

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

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.
Original languageEnglish
Title of host publicationProceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers
Publication date12 Aug 2016
ISBN (Print)978-1-945626-10-4
DOIs
Publication statusPublished - 12 Aug 2016
Externally publishedYes

Keywords

  • Cross-lingual pronoun prediction
  • WMT shared task 2016
  • Deep recurrent neural networks
  • Part-of-speech tagging
  • Lemmatization

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