Predicting future international events from textual information, such as news articles, has tremendous potential for applications in global policy, strategic decision-making, and geopolitics. However, existing datasets available for this task are often limited in quality, hindering the progress of related research. In this paper, we introduce WORLDREP (WORLD Relationship and Event Prediction), a novel dataset designed to address these limitations by leveraging the advanced reasoning capabilities of large-language models (LLMs). Our dataset features high-quality scoring labels generated through advanced prompt modeling and rigorously validated by domain experts in political science. We showcase the quality and utility of WORLDREP for real-world event prediction tasks, demonstrating its effectiveness through extensive experiments and analysis. Furthermore, we publicly release our dataset along with the full automation source code for data collection, labeling, and benchmarking, aiming to support and advance research in text-based event prediction.

People are silhouetted as they pose with laptops in front of a screen projected with a Google logo, in this picture illustration taken in Zenica October 29, 2014. BEIJING - "China is a rising country of AI work and research," said Fei-Fei Li, chief scientist of artificial intelligence and machine learning at Google Cloud, calling for enhanced AI cooperation between major countries. Li made the remarks in a recent exclusive interview with Xinhua at Google's Beijing office. Just last week, Li announced that Google would launch a new AI research center in Beijing, as part of its AI First strategy. When asked what prompted Google to make the decision to open its center in the Chinese capital, Li said: "We all recognize the importance of China because of its talent, because of the incredible creativity and innovation that are already going on here."