  In grammatical error correction (GEC), automatic evaluation is an important
factor for research and development of GEC systems. Previous studies on
automatic evaluation have demonstrated that quality estimation models built
from datasets with manual evaluation can achieve high performance in automatic
evaluation of English GEC without using reference sentences.. However, quality
estimation models have not yet been studied in Japanese, because there are no
datasets for constructing quality estimation models. Therefore, in this study,
we created a quality estimation dataset with manual evaluation to build an
automatic evaluation model for Japanese GEC. Moreover, we conducted a
meta-evaluation to verify the dataset's usefulness in building the Japanese
quality estimation model.
