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
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2021.law-1.6.pdf
- Code
- shirawein/spanish-english-amr-corpus