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 (Li et al., 2012), -combination of projection and type constraints (Das and Petrov, 2011;Täckström et al., 2013), -rapid annotation of seed training data .
only one or two compatible sources of distant supervision are typically employed.