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Evaluating Pronominal Anaphora in Machine Translation: An Evaluation Measure and a Test Suite
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
The neural revolution in machine translation has made it easier to model larger contexts beyond the sentence-level, which can potentially help resolve some discourse-level ambiguities such as pronominal anaphora, thus enabling better translations. Unfortunately, even when the resulting improvements are seen as substantial by humans, they remain virtually unnoticed by traditional automatic evaluation measures such as BLEU, as only a few words end up being affected. Thus, specialized evaluation
doi:10.18653/v1/d19-1294
dblp:conf/emnlp/JwalapuramJTN19
fatcat:apjb37qq2venfkqtblirydm3xy