generative commonsense reasoning refers to the task of generating acceptable
and logical assumptions about everyday situations based on commonsense
understanding. By utilizing an existing dataset such as korean commonge
本论文中,我们探讨如何运用常识知识图谱提高条件文本生成模型的综合性能,通过从 Conceptnet 中提取常识关系,将这些关系注入到 Unified Language Model (UniLM) 中,并通过输出约束强制实施词汇要求,以提高生成文本的语义正确性和符合人类理解,从而实现了匹配词性和完全概念覆盖的要求。