Abstract

Data scarcity has been a long standing issue in the field of open-domain social dialogue. To quench this thirst, we present Soda: the first publicly available, million-scale high-quality social dialogue dataset. By contextualizing social commonsense knowledge from a knowledge graph, we are able to distill an exceptionally broad spectrum of social interactions from a large language model. Human evaluation shows that conversations in Soda are more consistent, specific, and (surprisingly) natural than those in prior human-authored datasets.