Multilingual Grammatical Error Annotation: Combining Language-Agnostic Framework With Language-Specific Flexibility

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.

Recommended citation: Qiu, M., Nguyen, T. M., Huang, Z., Li, Z., Gu, Y., Gao, Q., Liu, S., & Park, J. (2025). Multilingual grammatical error annotation: Combining language-agnostic framework with language-specific flexibility. Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications, 202–212. https://doi.org/10.18653/v1/2025.bea-1.15
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