On Language Spaces, Scales and Cross-Lingual Transfer of UD Parsers

Abstract

Cross-lingual transfer of parsing models has been shown to work well for several closelyrelated languages, but predicting the success in other cases remains hard. Our study is a comprehensive analysis of the impact of linguistic distance on the transfer of Universal Dependencies (UD) parsers. As an alternative to syntactic typological distances extracted from URIEL, we propose three text-based feature spaces and show that they can be more precise predictors, especially on a more local scale, when only shorter distances are taken into account. Our analysis also reveals that the good coverage in typological databases is not among the factors that explain good transfer.