Basically, in this paper, we train the model with an encoder-decoder neural network and using dependencies in which the input of the source language is in sequence form and the output of the target language will be generated in a linearized dependency-based tree structure.
instead of predicting only words at each time step, the model trains the network to predict both words and their grammatical dependencies as a dependency tree at each time step.