In this paper, we present a straightforward strategy for transferring dependency parsers across languages. The proposed method learns a parser from partially annotated data obtained through the projection of annotations across unambiguous word alignments. It does not rely on any modeling of the reliability of dependency and/or alignment links and is therefore easy to implement and parameter free. Experiments on six languages show that our method is at par with recent algorithmically demanding methods, at a much cheaper computational cost. It can thus serve as a fair baseline for transferring dependencies across languages with the use of parallel corpora.
REF describe a method for transferring dependency parsers across languages by projecting annotations across word alignments and learning from the partially annotated data.
Frustratingly Easy Cross-Lingual Transfer for Transition-Based Dependency Parsing
HLT-NAACL
Computer Science