Back to Search Start Over

CLEME2.0: Towards More Interpretable Evaluation by Disentangling Edits for Grammatical Error Correction

Authors :
Ye, Jingheng
Xu, Zishan
Li, Yinghui
Cheng, Xuxin
Song, Linlin
Zhou, Qingyu
Zheng, Hai-Tao
Shen, Ying
Su, Xin
Publication Year :
2024

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.<br />Comment: 16 pages, 8 tables, 2 figures. Under review

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2407.00934
Document Type :
Working Paper