For the embedding representations of these two types of features, we use the embeddings of de Kok (2015), which were trained on corpora of 800 millions tokens, using WANG2VEC (Ling et al., 2015), a variation of WORD2VEC that is tailored to syntactic tasks.
(2007) that counts the number of words between the preposition and the candidate, with the logarithm of this distance and the relative distance.