We make use of the same graph neural network encoder structure to represent dependency syntax information for both the baseline and our model.
a graph recurrent neural network architecture (Beck et al., 2018; is used, which has been shown effective in encoding graph structures , giving competitive results with alternative graph networks such as graph convolutional neural networks Bastings et al., 2017).