Cross-lingual dependency parsing involves transferring syntactic knowledge\nfrom one language to another. It is a crucial component for inducing dependency\nparsers in low-resource scenarios where no training data for a language exists.\nUsing Faroese as the target language, we compare two approaches using\nannotation projection: first, projecting from multiple monolingual source\nmodels; second, projecting from a single polyglot model which is trained on the\ncombination of all source languages. Furthermore, we reproduce multi-source\nprojection (Tyers et al., 2018), in which dependency trees of multiple sources\nare combined. Finally, we apply multi-treebank modelling to the projected\ntreebanks, in addition to or alternatively to polyglot modelling on the source\nside. We find that polyglot training on the source languages produces an\noverall trend of better results on the target language but the single best\nresult for the target language is obtained by projecting from monolingual\nsource parsing models and then training multi-treebank POS tagging and parsing\nmodels on the target side.\n