It is intractable to evaluate the performance of Grammatical Error Correction (GEC) systems since GEC is a highly subjective task. Designing an evaluation metric that is as objective as possible is crucial to the development of GEC task. Previous mainstream evaluation metrics, i.e., reference-based metrics, introduce bias into the multi-reference evaluation because they extract edits without considering the presence of multiple references. To overcome the problem, we propose Chunk-LEvel Multi-reference Evaluation (CLEME) designed to evaluate GEC systems in multi-reference settings. First, CLEME builds chunk sequences with consistent boundaries for the source, the hypothesis and all the references, thus eliminating the bias caused by inconsistent edit boundaries. Then, based on the discovery that there exist boundaries between different grammatical errors, we automatically determine the grammatical error boundaries and compute F$_{0.5}$ scores in a novel way. Our proposed CLEME approach consistently and substantially outperforms existing reference-based GEC metrics on multiple reference sets in both corpus-level and sentence-level settings. Extensive experiments and detailed analyses demonstrate the correctness of our discovery and the effectiveness of our designed evaluation metric.

提出了一种Chunk-Level Multi-reference Evaluation (CLEME)方法，通过建立一致边界的块序列并自动确定语法错误边界，以评估多引用设置下的语法纠错系统的性能，CLEME方法在语料库级别和句子级别设置中比现有基于参考的GEC度量表现更好。

CLEME: 语法错误修正的去偏置多参考评估