It is difficult to transform prior knowledge represented in discrete forms to continuous representations required by neural networks.
a number of authors have endeavored to integrate prior knowledge into NMT in recent years, either by modifying model architectures Cohn et al., 2016;Tang et al., 2016;Feng et al., 2016) or by modifying training objectives (Cohn et al., 2016;Feng et al., 2016;.