GateNLP at SemEval-2025 Task 10: Hierarchical Three-Step Prompting for Multilingual Narrative Classification
Abstract
AbstractThe proliferation of online news and the increasing spread of misinformation necessitate robust methods for automated narrative classification. This paper presents our approach to SemEval 2025 Task 10 Subtask 2, which aims to classify news articles into a predefined two-level taxonomy of main narratives and sub-narratives across multiple languages. We propose Hierarchical Three-Step Prompting (H3Prompt) for multilingual narrative classification. Our methodology follows a three-step prompting strategy, where the model first categorises an article into one of two domains (Ukraine-Russia War or Climate Change), then identifies the most relevant main narratives, and finally assigns sub-narratives. Our approach secured the top position on the English test set among 28 competing teams worldwide. This result highlights the effectiveness of our method in improving narrative classification performance over the baselines.