@inproceedings{qiu-etal-2025-multilingual,
title = "Multilingual Grammatical Error Annotation: Combining Language-Agnostic Framework with Language-Specific Flexibility",
author = "Qiu, Mengyang and
Nguyen, Tran Minh and
Huang, Zihao and
Li, Zelong and
Gu, Yang and
Gao, Qingyu and
Liu, Siliang and
Park, Jungyeul",
editor = {Kochmar, Ekaterina and
Alhafni, Bashar and
Bexte, Marie and
Burstein, Jill and
Horbach, Andrea and
Laarmann-Quante, Ronja and
Tack, Ana{\"i}s and
Yaneva, Victoria and
Yuan, Zheng},
booktitle = "Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.bea-1.15/",
doi = "10.18653/v1/2025.bea-1.15",
pages = "202--212",
ISBN = "979-8-89176-270-1",
abstract = "Grammatical Error Correction (GEC) relies on accurate error annotation and evaluation, yet existing frameworks, such as errant, face limitations when extended to typologically diverse languages. In this paper, we introduce a standardized, modular framework for multilingual grammatical error annotation. Our approach combines a language-agnostic foundation with structured language-specific extensions, enabling both consistency and flexibility across languages. We reimplement errant using stanza to support broader multilingual coverage, and demonstrate the framework{'}s adaptability through applications to English, German, Czech, Korean, and Chinese, ranging from general-purpose annotation to more customized linguistic refinements. This work supports scalable and interpretable GEC annotation across languages and promotes more consistent evaluation in multilingual settings. The complete codebase and annotation tools can be accessed at https://github.com/open-writing-evaluation/jp{\_}errant{\_}bea."
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<abstract>Grammatical Error Correction (GEC) relies on accurate error annotation and evaluation, yet existing frameworks, such as errant, face limitations when extended to typologically diverse languages. In this paper, we introduce a standardized, modular framework for multilingual grammatical error annotation. Our approach combines a language-agnostic foundation with structured language-specific extensions, enabling both consistency and flexibility across languages. We reimplement errant using stanza to support broader multilingual coverage, and demonstrate the framework’s adaptability through applications to English, German, Czech, Korean, and Chinese, ranging from general-purpose annotation to more customized linguistic refinements. This work supports scalable and interpretable GEC annotation across languages and promotes more consistent evaluation in multilingual settings. The complete codebase and annotation tools can be accessed at https://github.com/open-writing-evaluation/jp_errant_bea.</abstract>
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%0 Conference Proceedings
%T Multilingual Grammatical Error Annotation: Combining Language-Agnostic Framework with Language-Specific Flexibility
%A Qiu, Mengyang
%A Nguyen, Tran Minh
%A Huang, Zihao
%A Li, Zelong
%A Gu, Yang
%A Gao, Qingyu
%A Liu, Siliang
%A Park, Jungyeul
%Y Kochmar, Ekaterina
%Y Alhafni, Bashar
%Y Bexte, Marie
%Y Burstein, Jill
%Y Horbach, Andrea
%Y Laarmann-Quante, Ronja
%Y Tack, Anaïs
%Y Yaneva, Victoria
%Y Yuan, Zheng
%S Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-270-1
%F qiu-etal-2025-multilingual
%X Grammatical Error Correction (GEC) relies on accurate error annotation and evaluation, yet existing frameworks, such as errant, face limitations when extended to typologically diverse languages. In this paper, we introduce a standardized, modular framework for multilingual grammatical error annotation. Our approach combines a language-agnostic foundation with structured language-specific extensions, enabling both consistency and flexibility across languages. We reimplement errant using stanza to support broader multilingual coverage, and demonstrate the framework’s adaptability through applications to English, German, Czech, Korean, and Chinese, ranging from general-purpose annotation to more customized linguistic refinements. This work supports scalable and interpretable GEC annotation across languages and promotes more consistent evaluation in multilingual settings. The complete codebase and annotation tools can be accessed at https://github.com/open-writing-evaluation/jp_errant_bea.
%R 10.18653/v1/2025.bea-1.15
%U https://aclanthology.org/2025.bea-1.15/
%U https://doi.org/10.18653/v1/2025.bea-1.15
%P 202-212
Markdown (Informal)
[Multilingual Grammatical Error Annotation: Combining Language-Agnostic Framework with Language-Specific Flexibility](https://aclanthology.org/2025.bea-1.15/) (Qiu et al., BEA 2025)
ACL
- Mengyang Qiu, Tran Minh Nguyen, Zihao Huang, Zelong Li, Yang Gu, Qingyu Gao, Siliang Liu, and Jungyeul Park. 2025. Multilingual Grammatical Error Annotation: Combining Language-Agnostic Framework with Language-Specific Flexibility. In Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2025), pages 202–212, Vienna, Austria. Association for Computational Linguistics.