The input embeddings of our parser are also trained over large raw text, and in this perspective our model is correlated with the semi-supervised models.
because we fine-tune the word embeddings in supervised training, the embeddings of in-vocabulary words become systematically different from these of out-of-vocabulary words after training, and the effect of pre-trained out-ofvocabulary embeddings become uncertain.