Basic Feature Setting -where we set basic features that indicate whether an arc is likely to be connecting a coreferent pair by adapting the features used by dos Santos and Carvalho (2011); Context Feature Induction -where we conjoin basic features to generate complex features with high discriminating power by means of the entropy-guided feature induction method proposed by  and Milidiú, dos Santos, and Duarte (2008); and Coreference Tree Learning -where we learn how to extract the trees that connect coreferent mentions in the graph of mentions by applying a large margin latent perceptron structure learning algorithm.
additionally, we see that our method seems to converge before 50 epochs, which is the number of epochs used to train all models used in this work.