Systems that rely on neural machine translation (Yuan and Briscoe, 2016;Xie et al., 2016;Schmaltz et al., 2017;Ji et al., 2017) are not yet able to achieve as high performance as SMT systems according to automatic evaluation metrics (see Table 1 for comparison on the CoNLL-2014 test set).
it has been shown that the neural approach can produce more fluent output, which might be desirable by human evaluators (Napoles et al., 2017).