We study the effectiveness of Knowledge Graph Embeddings (KGE) for knowledge graph (KG) completion with rule mining. More specifically, we mine rules from KGs before and after they have been completed by a KGE to compare possible differences in the rules extracted. We apply this method to classical KGEs approaches, in particular, TransE, DistMult and ComplEx. Our experiments indicate that there can be huge differences between the extracted rules, depending on the KGE approach for KG completion. In particular, after the TransE completion, several spurious rules were extracted.

翻译：我们研究了知识图嵌入(KGE)在以规则采矿完成知识图(KG)方面的有效性,更具体地说,我们在KGE完成之前和之后对KGs的规则进行采矿,以比较所提取规则中可能的差异;我们将这一方法应用于传统的KGes方法,特别是TransE、DistMult和ComplEx。我们的实验表明,根据KGE完成规则的方法,所提取的规则之间可能存在巨大差异。特别是,在TransE完成之后,我们提取了几项虚假规则。