After pre-processing, distributed representations of all tokens and lemmas were obtained from a skip-gram (Mikolov et al., 2013) model.
the gensim (Řehůřek and Sojka, 2010) implementation of skip-gram was trained on a snapshot of Wikipedia from September 2015 to learn 100 dimensional word embeddings.