In order to do this, we adopt a multi-task learning approach (Collobert et al., 2011;Yang et al., 2016;Bingel and Søgaard, 2017;Martínez Alonso and Plank, 2017).
we use parameter sharing in the hidden layers of our bi-LSTM model so that we can generate a unified model that can carry information beneficial to each task.