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
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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 submissions outperformed two strong language-model based baseline systems, with systems using deep recurrent neural networks outperforming those using other architectures for most language pairs.