Ontological knowledge, which comprises classes and properties and their relationships, is integral to world knowledge. It is significant to explore whether Pretrained Language Models (PLMs) know and understand such knowledge. However, existing PLM-probing studies focus mainly on factual knowledge, lacking a systematic probing of ontological knowledge. In this paper, we focus on probing whether PLMs store ontological knowledge and have a semantic understanding of the knowledge rather than rote memorization of the surface form. To probe whether PLMs know ontological knowledge, we investigate how well PLMs memorize: (1) types of entities; (2) hierarchical relationships among classes and properties, e.g., Person is a subclass of Animal and Member of Sports Team is a subproperty of Member of ; (3) domain and range constraints of properties, e.g., the subject of Member of Sports Team should be a Person and the object should be a Sports Team. To further probe whether PLMs truly understand ontological knowledge beyond memorization, we comprehensively study whether they can reliably perform logical reasoning with given knowledge according to ontological entailment rules. Our probing results show that PLMs can memorize certain ontological knowledge and utilize implicit knowledge in reasoning. However, both the memorizing and reasoning performances are less than perfect, indicating incomplete knowledge and understanding.

翻译：本体论知识由类、属性及其相互关系构成，是世界知识的重要组成部分。探究预训练语言模型（PLMs）是否知晓并理解此类知识具有重要研究价值。然而现有PLM探测研究主要聚焦事实性知识，缺乏对本体论知识的系统性探测。本文重点探究PLM是否存储本体论知识，以及是否具备对该知识的语义理解而非机械记忆。为探测PLM是否知晓本体论知识，我们从以下维度考察模型记忆能力：（1）实体类型；（2）类与属性间的层次关系（例如"人"是"动物"的子类，"运动队成员"是"成员"的子属性）；（3）属性的定义域与值域约束（例如"运动队成员"的主语应为"人"，宾语应为"运动队"）。为进一步探究PLM是否超越机械记忆而真正理解本体论知识，我们全面研究了模型能否根据本体论蕴含规则，利用给定知识进行可靠的逻辑推理。探测结果表明，PLM能够记忆部分本体论知识并在推理中运用隐含知识，但记忆与推理表现均未臻完美，表明模型存在知识不完备与理解不充分的问题。