Fine-Grained Analysis of Cross-Linguistic Syntactic Divergences

Dmitry Nikolaev, Ofir Arviv, Taelin Karidi, Neta Kenneth, Veronika Mitnik, Lilja Maria Saeboe, Omri Abend


Abstract
The patterns in which the syntax of different languages converges and diverges are often used to inform work on cross-lingual transfer. Nevertheless, little empirical work has been done on quantifying the prevalence of different syntactic divergences across language pairs. We propose a framework for extracting divergence patterns for any language pair from a parallel corpus, building on Universal Dependencies. We show that our framework provides a detailed picture of cross-language divergences, generalizes previous approaches, and lends itself to full automation. We further present a novel dataset, a manually word-aligned subset of the Parallel UD corpus in five languages, and use it to perform a detailed corpus study. We demonstrate the usefulness of the resulting analysis by showing that it can help account for performance patterns of a cross-lingual parser.
Anthology ID:
2020.acl-main.109
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1159–1176
Language:
URL:
https://aclanthology.org/2020.acl-main.109
DOI:
10.18653/v1/2020.acl-main.109
Bibkey:
Cite (ACL):
Dmitry Nikolaev, Ofir Arviv, Taelin Karidi, Neta Kenneth, Veronika Mitnik, Lilja Maria Saeboe, and Omri Abend. 2020. Fine-Grained Analysis of Cross-Linguistic Syntactic Divergences. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 1159–1176, Online. Association for Computational Linguistics.
Cite (Informal):
Fine-Grained Analysis of Cross-Linguistic Syntactic Divergences (Nikolaev et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.109.pdf
Dataset:
 2020.acl-main.109.Dataset.zip
Video:
 http://slideslive.com/38928779
Code
 macleginn/exploring-clmd-divergences
Data
Universal Dependencies