Temporal facts, which are used to describe events that occur during specific
time periods, have become a topic of increased interest in the field of
knowledge graph (KG) research. In terms of quality management, the introduction
of time restrictions brings new challenges to maintaining the temporal
consistency of KGs. Previous studies rely on manually enumerated temporal
constraints to detect conflicts, which are labor-intensive and may have
granularity issues. To address this problem, we start from the common pattern
of temporal facts and propose a pattern-based temporal constraint mining
method, PaTeCon. Unlike previous studies, PaTeCon uses graph patterns and
statistical information relevant to the given KG to automatically generate
temporal constraints, without the need for human experts. In this paper, we
illustrate how this method can be optimized to achieve significant speed
improvement. We also annotate Wikidata and Freebase to build two new benchmarks
for conflict detection. Extensive experiments demonstrate that our
pattern-based automatic constraint mining approach is highly effective in
generating valuable temporal constraints.

通过基于模式的时间约束挖掘方法，本研究在知识图谱研究领域开发了一种自动生成有关时间的约束规则的方法，用于解决时间约束对知识图谱一致性的影响，并通过构建两个新的冲突检测基准数据集，证明了该方法在生成有用的时间约束方面的高效性。