It combines the advantages of the cross-lingual annotation projection methods, which project labeled information into the target language domain, and the cross-lingual representation learning methods, which learn latent interlingual features.
we first train a dependency parser on the labeled source language data and use it to infer labels for the unlabeled source language sentences of the parallel resources.