We employ the same model architecture as Kiperwasser and Goldberg (2016a).
we first use a bi-LSTM to encode an n-token sentence, treated as a sequence of per-token concatenations of word-and POS-tag embeddings, into a sequence of vectors is the output of the bi-LSTM at time step i.