1. CLEME2.0: Towards More Interpretable Evaluation by Disentangling Edits for Grammatical Error Correction
- Author
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Ye, Jingheng, Xu, Zishan, Li, Yinghui, Cheng, Xuxin, Song, Linlin, Zhou, Qingyu, Zheng, Hai-Tao, Shen, Ying, and Su, Xin
- Subjects
Computer Science - Computation and Language - Abstract
The paper focuses on improving the interpretability of Grammatical Error Correction (GEC) metrics, which receives little attention in previous studies. To bridge the gap, we propose CLEME2.0, a reference-based evaluation strategy that can describe four elementary dimensions of GEC systems, namely hit-correction, error-correction, under-correction, and over-correction. They collectively contribute to revealing the critical characteristics and locating drawbacks of GEC systems. Evaluating systems by Combining these dimensions leads to high human consistency over other reference-based and reference-less metrics. Extensive experiments on 2 human judgement datasets and 6 reference datasets demonstrate the effectiveness and robustness of our method. All the codes will be released after the peer review., Comment: 16 pages, 8 tables, 2 figures. Under review
- Published
- 2024