We adopt the general encoder architecture from these works, constructing word representations from characters and using another bidirectional LSTM to encode the context vectors.
for each word in a sentence, the decoder uses a unidirectional LSTM network (figure 1 (c)) to generate a sequence of morphological category-value pairs based on the context vector h and the previous predictions.