In this paper, we present CogNet2, an extension of the CogNet knowledge base, which combines the significant events form Wikidata, entities from YAGO4 and commonsense assertions from ATOMIC. It aims to unify knowledge of multiple levels of granularity. To efficiently integrate significant event and entity knowledge into CogNet, we construct significant event- and entity-centric frames, and then link them to the CogNet by automated labeling and crowd-sourced annotation. To enrich CogNet with more commonsense knowledge in social interaction, we construct frames with element restriction for fine-grained typical situations and integrate commonsense assertions about them. As a result, in comparison with CogNet1, CogNet2 increases 800+ new frames of significant events and entities, 30000+ new fine-grained frames with element restrictions, more than 204K new commonsense assertions. The scale of frame instances is up to 33.4M in total