Furthermore, English as source language produces higher numbers of ambiguous words compared to English as target language.
recent works suggest that the state-of-the-art Transformer architecture (Vaswani et al., 2017) for neural MT (NMT) is able to deal with lexical ambiguity quite well (Tang et al., 2018;Tang et al., 2019), learning to distinguish between senses during translation with high precision.