This paper presents a solution to the GenChal 2022 shared task dedicated to feedback comment generation for writing learning. In terms of this task given a text with an error and a span of the error, a system generates an explanatory note that helps the writer (language learner) to improve their writing skills. Our solution is based on fine-tuning the T5 model on the initial dataset augmented according to syntactical dependencies of the words located within indicated error span. The solution of our team "nigula" obtained second place according to manual evaluation by the organizers.

翻译：本文为GenChal 2022 共同任务提供了解决方案, 用于生成用于写作学习的反馈评论生成。 根据该任务给出了一个错误和跨度的文本, 一个系统生成了一个解释性说明, 帮助写作者( 语言学习者) 提高写作技能。 我们的解决方案基于对根据标出错误范围内的单词的综合依赖性而扩大的初始数据集的T5模型进行微调。 根据组织者的手工评估, 我们团队的“ nigula” 解决方案获得第二名 。