Current frontier LLMs struggle with social forecasting (max 75/100), and their strengths in probability calibration don't guarantee temporal accuracy—revealing a gap between understanding likelihood and timing in real-world events.
SocietyBench is a benchmark that tests how well LLMs can forecast social events by understanding real-world timelines. It anonymizes events by replacing names and shifting dates to prevent models from relying on memorized information, then scores predictions on probability calibration and temporal accuracy across five real events in Chinese and English.