Synthetic Treebanking for Cross Lingual Dependency Parsing
How do we parse the languages for which no treebanks are available? This contribution addresses the cross lingual viewpoint on statistical dependency parsing, in which we attempt to make use of resource rich source language treebanks to build and adapt models for the under resourced target languages. We outline the benefits, and indicate the drawbacks of the current major approaches. We emphasize synthetic treebanking: the automatic creation of target language treebanks by means of annotation projection and machine translation. We present competitive results in cross lingual dependency parsing using a combination of various techniques that contribute to the overall success of the method. We further include a detailed discussion about the impact of part of speech label accuracy on parsing results that provide guidance in practical applications of cross lingual methods for truly under resourced languages.
J. Artif. Intell. Res.