Omkar2118/datasets huggingface dataset:
WikiFactDiff

WikiFactDiff is a dataset designed as a resource to perform atomic factual knowledge updates on language models, with the goal of aligning them with current knowledge. It describes the evolution of factual knowledge between two dates, named T_old and T_new,​ in the form of semantic triples. To enable the possibility of evaluating knowledge algorithms (such as ROME, MEND, MEMIT, etc.), these triples are verbalized and neighbor facts are determined to check for eventual bleedover.

Introducing paper: WikiFactDiff: A Large, Realistic, and Temporally Adaptable Dataset for Atomic Factual Knowledge Update in Causal Language Models