【摘要】 开放文本中蕴含着大量的逻辑性知识,以刻画事物之间逻辑传导关系的逻辑类知识库是推动知识推理发展的重要基础,研发大规模逻辑推理知识库有助于支持由实体或事件等传导驱动的决策任务。该文围绕逻辑推理知识库,论述了知识库的概念、类别和基本构成,提出了一种面向大规模开放文本的实体描述、事件因果逻辑知识快速抽取方法;面向金融领域,探索了一套基于逻辑推理知识库的可解释性路径推理方法和金融实体影响生成系统。算法模型和系统均取得了不错的效果。更多还原

【Abstract】 There are a large amount of logical knowledge that portray the logical evolutionary relationships between things in the open texts. Logical knowledge bases are an important foundation to advancing the knowledge reasoning, the development of large-scale logical reasoning knowledge bases can help support conduction-driven decision-making tasks for entities or events. This paper presents an overview of the logical knowledge base, including categories and basic compositions. It also proposes a method for entity description and event causal logical knowledge extraction from the large-scale open text. Finally, a reliable interpretable path reasoning algorithm and financial entity influence generation system based on the logical reasoning knowledge base is explored for the financial domain. The algorithm model and system have achieved good results.更多还原