Encoders Help You Disambiguate Word Senses in Neural Machine Translation (D19-1)
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| Challenge: | Neural machine translation models can perform word sense disambiguation (WSD) however, it is unclear which component dominates the process of disambiguating words. |
| Approach: | They evaluate hidden states and investigate distributions of self-attention in NMT encoders and decoders to disambiguate word senses. |
| Outcome: | The proposed model outperforms encoder hidden states on large datasets . the model outpersforms decoders on large data sets . |
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