To compensate for the absence of direct supervision, work in crosslingual learning and distant supervision has discovered creative use for a number of alternative data sources to learn feasible models: -aligned parallel corpora to project POS annotations to target languages (Yarowsky et al., 2001; Agić et al., 2015; Fang and Cohn, 2016) , -noisy tag dictionaries for type-level approximation of full supervision<cite> (Li et al., 2012)</cite> , -combination of projection and type constraints (Das and Petrov, 2011; Täckström et al., 2013) , -rapid annotation of seed training data .