mlsanityData to 7 Oct 2026

Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling

arXiv 2411.14042 ↗First posted 21 Nov 2024cs.CL cs.AIcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 27 of its 43 references that are in the map. First posted on arXiv 21 Nov 2024.

Builds on

27 of 43 references.

References · 27

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15 more
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Citing papers per year: 2025: 1.

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  1. 2025Revisiting LLMs as Zero-Shot Time-Series Forecasters: Small Noise Can Break Large Modelscited by 7

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  1. 2024MIRAI: Evaluating LLM Agents for Event Forecasting
  2. 2026ThinkTank-ME: A Multi-Expert Framework for Middle East Event Forecasting
  3. 2024A Comprehensive Evaluation of Large Language Models on Temporal Event Forecasting
  4. 2024MM-Forecast: A Multimodal Approach to Temporal Event Forecasting with Large Language Models
  5. 2026ForecastAgentSearch: Towards a Multi-Expert Agent Search System for Geopolitical Event Forecasting
  6. 2025Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts
  7. 2026WorldReasoner: Evaluating Whether Language Model Agents Forecast Events with Valid Reasoning
  8. 2024From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection