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arXiv 1911.12091cs.CLcs.AIcs.IR

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

LMU Munich(慕尼黑大学);Uppsala University(乌普萨拉大学);Qatar Computing Res. Inst.(卡塔尔计算研究所);HBKU(哈马德·本·哈利法大学);University of Helsinki(赫尔辛基大学);LinkedIn(领英);Fondazione Bruno Kessler(布鲁诺·凯斯勒基金会);Idiap Research Institute(伊迪亚普研究所)

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

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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