We aim to determine which temporal instance queries can be uniquely
characterised by a (polynomial-size) set of positive and negative temporal data
examples. We start by considering queries formulated in fragments of
propositional linear temporal logic LTL that correspond to conjunctive queries
(CQs) or extensions thereof induced by the until operator. Not all of these
queries admit polynomial characterisations but by restricting them further to
path-shaped queries we identify natural classes that do. We then investigate
how far the obtained characterisations can be lifted to temporal knowledge
graphs queried by 2D languages combining LTL with concepts in description
logics EL or ELI (i.e., tree-shaped CQs). While temporal operators in the scope
of description logic constructors can destroy polynomial characterisability, we
obtain general transfer results for the case when description logic
constructors are within the scope of temporal operators. Finally, we apply our
characterisations to establish (polynomial) learnability of temporal instance
queries using membership queries in the active learning framework.

通过分析命题线性时间逻辑 LTL 与 EL 或 ELI 描述逻辑中的概念结合的 2D 语言所查询的时间知识图中的路径形查询，研究了一些查询操作可以通过（多项式大小的）正 / 负时间数据示例的集合来唯一地描述的可能性，探讨了这些查询的多项式特性，并将其应用于活性学习框架中对时间实例查询的学习。