Cross-lingual transfer of semantic role labeling models

Semantic Role Labeling (SRL) has become one of the standard tasks of natural language processing and proven useful as a source of information for a number of other applications.We address the problem of transferring an SRL model from one language to another using a shared feature representation.This approach is then evaluated on three language pairs, demonstrating competitive performance as compared to a state-of-the-art unsupervised SRL system and a cross-lingual annotation projection baseline.We also consider the contribution of different aspects of the feature representation to the performance of the model and discuss practical applicability of this method.