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 language | English |
|---|---|
| Title of host publication | Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers |
| Publication date | 12 Aug 2016 |
| ISBN (Print) | 978-1-945626-10-4 |
| DOIs | |
| Publication status | Published - 12 Aug 2016 |
| Externally published | Yes |
Keywords
- Cross-lingual pronoun prediction
- WMT shared task 2016
- Deep recurrent neural networks
- Part-of-speech tagging
- Lemmatization
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