Classifying Divergences in Cross-lingual AMR Pairs

Shira Wein, Nathan Schneider


Abstract
Translation divergences are varied and widespread, challenging approaches that rely on parallel text. To annotate translation divergences, we propose a schema grounded in the Abstract Meaning Representation (AMR), a sentence-level semantic framework instantiated for a number of languages. By comparing parallel AMR graphs, we can identify specific points of divergence. Each divergence is labeled with both a type and a cause. We release a small corpus of annotated English-Spanish data, and analyze the annotations in our corpus.
Anthology ID:
2021.law-1.6
Volume:
Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Editors:
Claire Bonial, Nianwen Xue
Venue:
LAW
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
56–65
Language:
URL:
https://aclanthology.org/2021.law-1.6
DOI:
10.18653/v1/2021.law-1.6
Bibkey:
Cite (ACL):
Shira Wein and Nathan Schneider. 2021. Classifying Divergences in Cross-lingual AMR Pairs. In Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop, pages 56–65, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Classifying Divergences in Cross-lingual AMR Pairs (Wein & Schneider, LAW 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.law-1.6.pdf
Code
 shirawein/spanish-english-amr-corpus