CATCH-ME

CATCH-ME dataset: multilingual multi-turn counterspeech against hate speech and misinformation for RAG systems

Researchers introduce CATCH-ME, a large-scale expert-curated multilingual dataset of multi-turn dialogues addressing the intersection of hate speech and misinformation across five languages and seven marginalized groups. The dataset is anchored in verified external knowledge (fact-checking articles and NGO reports) with document- and chunk-level span annotations, making it directly usable for RAG-based counterspeech systems. It addresses a gap in existing resources, which are limited to single-turn English dialogues, and is intended to improve the factual grounding and persuasiveness of LLM-generated counterspeech.