Much previous work propose to improve the NMT model by adopting fine-grained translation levels such as the character or sub-word levels, which can learn the intermediate information inside words (Ling et al., 2015;Costa-jussà and Fonollosa, 2016;Chung et al., 2016;Luong et al., 2016;Lee et al., 2016;García-Martínez et al., 2016).
high level structures such as phrases has not been explicitly explored in NMT, which is very useful for machine translation (Koehn et al., 2007).