PeaCoK is a project that creates a big network of common knowledge about different personas, with around 100,000 facts that have been checked by humans. It organizes this knowledge into five categories based on how people interact, and it gets this information from existing networks of common knowledge and computer models that have been trained on large amounts of data. The project shows that this network can help create more realistic and engaging stories or conversations in digital systems.

PeaCoK is a large-scale persona commonsense knowledge graph, containing approximately 100K human-validated persona facts. It schematizes five dimensions of persona knowledge identified in previous studies of human interactive behaviours, and distils facts in this schema from both existing commonsense knowledge graphs and large-scale pretrained language models. The analysis indicates that PeaCoK contains rich and precise world persona inferences that help downstream systems generate more consistent and engaging narratives.