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Re:GraphGPT: Extrapolating knowledge graphs from unstructure... by gryn on Wednesday February 01, 2023 @03:39AM (#34608000)
you can have a date_start and date_end to handle this ambiguity. but yes the complexity lies in the interpreter/reasoner that has to deal with these facts and evolution of this (meta)schema.

But rdf style and labeled property graph data modeling approach have multiple ways of dealing with this.

Re:GraphGPT: Extrapolating knowledge graphs from unstructure... by babelchips on Wednesday February 01, 2023 @04:12AM (#34608204)
The way Datomic handles facts, accumulating them and providing point-in-time queries, is very effective.

Facts can contradict each other. Old facts are not lost. Querying requires a notion of time - “as of”.

Re:GraphGPT: Extrapolating knowledge graphs from unstructure... by jaygray0919 on Wednesday February 01, 2023 @05:36AM (#34608772)
Correctomundo. See RDF-Star for progress about state-in-time. During summer 2022 there was extensive discussion/consideration in the W3C working group about different state-conditions.
Re:GraphGPT: Extrapolating knowledge graphs from unstructure... by zcw100 on Sunday February 05, 2023 @12:56PM (#34667038)
It's a combination of reification and bitemporal modeling.