Publication: Improving Word Sense Disambiguation in Neural Machine Translation with Sense Embeddings
Improving Word Sense Disambiguation in Neural Machine Translation with Sense Embeddings
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Rios, A., Mascarell, L., & Sennrich, R. (2017). Improving Word Sense Disambiguation in Neural Machine Translation with Sense Embeddings. 11–19. http://www.aclweb.org/anthology/W17-4702
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Abstract
Word sense disambiguation is necessary in translation because different word senses often have different translations. Neural machine translation models learn different senses of words as part of an end-to-end translation task, and their capability to perform word sense disambiguation has so far not been quantified. We exploit the fact that neural translation models can score arbitrary translations to design a novel cross-lingual word sense disambiguation task that is tailored towards evaluating neural machine translation models. We p
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Rios, A., Mascarell, L., & Sennrich, R. (2017). Improving Word Sense Disambiguation in Neural Machine Translation with Sense Embeddings. 11–19. http://www.aclweb.org/anthology/W17-4702
