@inproceedings{wein-schneider-2021-classifying,
title = "Classifying Divergences in Cross-lingual {AMR} Pairs",
author = "Wein, Shira and
Schneider, Nathan",
editor = "Bonial, Claire and
Xue, Nianwen",
booktitle = "Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.law-1.6",
doi = "10.18653/v1/2021.law-1.6",
pages = "56--65",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Classifying Divergences in Cross-lingual AMR Pairs
%A Wein, Shira
%A Schneider, Nathan
%Y Bonial, Claire
%Y Xue, Nianwen
%S Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F wein-schneider-2021-classifying
%X 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.
%R 10.18653/v1/2021.law-1.6
%U https://aclanthology.org/2021.law-1.6
%U https://doi.org/10.18653/v1/2021.law-1.6
%P 56-65
Markdown (Informal)
[Classifying Divergences in Cross-lingual AMR Pairs](https://aclanthology.org/2021.law-1.6) (Wein & Schneider, LAW 2021)
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.