English

On the Relation between Syntactic Divergence and Zero-Shot Performance

Computation and Language 2021-10-12 v1 Machine Learning

Abstract

We explore the link between the extent to which syntactic relations are preserved in translation and the ease of correctly constructing a parse tree in a zero-shot setting. While previous work suggests such a relation, it tends to focus on the macro level and not on the level of individual edges-a gap we aim to address. As a test case, we take the transfer of Universal Dependencies (UD) parsing from English to a diverse set of languages and conduct two sets of experiments. In one, we analyze zero-shot performance based on the extent to which English source edges are preserved in translation. In another, we apply three linguistically motivated transformations to UD, creating more cross-lingually stable versions of it, and assess their zero-shot parsability. In order to compare parsing performance across different schemes, we perform extrinsic evaluation on the downstream task of cross-lingual relation extraction (RE) using a subset of a popular English RE benchmark translated to Russian and Korean. In both sets of experiments, our results suggest a strong relation between cross-lingual stability and zero-shot parsing performance.

Keywords

Cite

@article{arxiv.2110.04644,
  title  = {On the Relation between Syntactic Divergence and Zero-Shot Performance},
  author = {Ofir Arviv and Dmitry Nikolaev and Taelin Karidi and Omri Abend},
  journal= {arXiv preprint arXiv:2110.04644},
  year   = {2021}
}

Comments

Accepted to EMNLP 2021

R2 v1 2026-06-24T06:45:53.648Z