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