The weights are learned by a multilayer perceptron that estimates the likelihood of the alignment between the predicted word and each of the input words: This model is enriched with additional linguistic features on input, as proposed by Sennrich and Haddow (2016).
we select the following which are proven as useful in prior work, and also relevant to our experiment: word form, POS tag, and dependency relations.