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Cross-lingual dependency parsing involves transferring syntactic knowledgefrom one language to another. It is a crucial component for inducing dependencyparsers in low-resource scenarios where no training data for a language exists.Using Faroese as the target language, we compare two approaches usingannotation projection: first, projecting from multiple monolingual sourcemodels; second, projecting from a single polyglot model which is trained on thecombination of all source languages. Furthermore, we reproduce multi-sourceprojection (Tyers et al., 2018), in which dependency trees of multiple sourcesare combined. Finally, we apply multi-treebank modelling to the projectedtreebanks, in addition to or alternatively to polyglot modelling on the sourceside. We find that polyglot training on the source languages produces anoverall trend of better results on the target language but the single bestresult for the target language is obtained by projecting from monolingualsource parsing models and then training multi-treebank POS tagging and parsingmodels on the target side.

Cross-lingual Parsing with Polyglot Training and Multi-treebank Learning: A Faroese Case Study