Findings of the 2016 WMT Shared Task on Cross-lingual Pronoun Prediction
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Nov 2019.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 1; 2025: 1.
5 papers.
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- 2024Mention Attention for Pronoun Translationcited by 0
- 2025DOLFIN -- Document-Level Financial test set for Machine Translation5 Feb 2025
- 2024Mention Attention for Pronoun Translation19 Dec 2024
- 2021Gender Bias Amplification During Speed-Quality Optimization in Neural Machine Translation1 Jun 2021
- 2021Repairing Pronouns in Translation with BERT-Based Post-Editing23 Mar 2021
- 2021Translating the Unseen? Yoruba-English MT in Low-Resource, Morphologically-Unmarked Settings7 Mar 2021