Annotation projection-based representation learning for cross-lingual dependency parsing

Abstract

Cross-lingual dependency parsing aims to train a dependency parser for an annotation-scarce target language by exploiting annotated training data from an annotation-rich source language, which is of great importance in the field of natural language processing. In this paper, we propose to address cross-lingual dependency parsing by inducing latent cross-lingual data representations via matrix completion and annotation projections on a large amount of unlabeled parallel sentences. To evaluate the proposed learning technique, we conduct experiments on a set of cross-lingual dependency parsing tasks with nine different languages. The experimental results demonstrate the efficacy of the proposed learning method for cross-lingual dependency parsing.