A Layered Taxonomy for Chinese Learner Grammatical Error Annotation
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Computer Science > Computation and Language
Title:A Layered Taxonomy for Chinese Learner Grammatical Error Annotation
Abstract:Grammatical error annotation in Chinese learner writing requires labels that are both consistent and linguistically meaningful. This paper proposes a layered scheme linking computational Chinese grammatical error correction (CGEC) with pedagogical error analysis. The scheme first identifies character- and punctuation-level orthographic errors, labeling them by edit operation and subtype. Other errors receive a three-layer core label combining edit operation, linguistic domain, and part of speech, with optional Chinese-specific extensions for aspect, modality, comparison, argument structure, and complements. Drawing on CGEC resources, learner-error taxonomies, and Mandarin grammar, the taxonomy is evaluated through a coverage analysis of automatically extracted MuCGEC edits and a preliminary consistency study in which five large language models apply it to a sample. The results support the layered approach while identifying category boundaries requiring further refinement.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2609.02153 [cs.CL] |
| (or arXiv:2609.02153v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2609.02153
arXiv-issued DOI via DataCite (pending registration)
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