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Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments
2018
Proceedings of the Third Conference on Machine Translation: Research Papers
Cross-sentence context can provide valuable information in Machine Translation and is critical for translation of anaphoric pronouns and for providing consistent translations. In this paper, we devise simple oracle experiments targeting coreference and coherence. Oracles are an easy way to evaluate the effect of different discourse-level phenomena in NMT using BLEU and eliminate the necessity to manually define challenge sets for this purpose. We propose two context-aware NMT models and compare
doi:10.18653/v1/w18-6306
dblp:conf/wmt/StojanovskiF18
fatcat:3glwodxidfe5bougllo5pouq7a