These consist of a i and a j , the LSTM-based representations for w i and w j (see Equation (4)), and their word and part-ofspeech embeddings, x i and x j (see Equation 3).
we use a trained DENSE model to go through the training corpus and generate features and corresponding dependency labels as training data.