What's happening in Myanmar's civil war as military holds elections? Voters in parts of Myanmar are heading to the polls on Sunday for an election that critics view as a bid by the country's generals to legitimise military rule, nearly five years after they overthrew the government of Nobel Laureate Aung San Suu Kyi. The multi-phased election is unfolding amid a raging civil war, with ethnic armed groups and opposition militias fighting the military for control of vast stretches of territory, stretching from the borderlands with Bangladesh and India in the west, across the central plains, to the frontiers with China and Thailand in the north and east. Another third will be covered during a second and third phase in January, while voting has been cancelled altogether in the remainder. Fighting, including air raids and arson, has intensified in several areas.

It was a Monday night in Myanmar's Chang U township in the central Sagaing region, where nearly 100 people had gathered to mark Thadingyut, the festival of the full moon. Some held candles at the event, which doubled as both a celebration and a protest against the military, which seized power in 2021, plunging the country into a bloody civil war. But the celebration soon turned into horror as a motorised paraglider - known locally as a paramotor - flew overhead and dropped bombs onto the crowd. The attack lasted just seven minutes, but at least 26 people died as a result and dozens more were injured. Initially, I thought the lower part of my body had been severed, one 30-year-old who was at the gathering told news agency Reuters.

Event annotation is important for identifying market changes, monitoring breaking news, and understanding sociological trends. Although expert annotators set the gold standards, human coding is expensive and inefficient. Unlike information extraction experiments that focus on single contexts, we evaluate a holistic workflow that removes irrelevant documents, merges documents about the same event, and annotates the events. Although LLM-based automated annotations are better than traditional TF-IDF-based methods or Event Set Curation, they are still not reliable annotators compared to human experts. However, adding LLMs to assist experts for Event Set Curation can reduce the time and mental effort required for Variable Annotation. When using LLMs to extract event variables to assist expert annotators, they agree more with the extracted variables than fully automated LLMs for annotation.