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-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPublication milestones
- Published - 12/08/2016
Publication status
Published - 12/08/2016
ISBN (Print)
978-1-945626-10-4Publication 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 PapersAbstract
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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