NORMSAGE: Multi-Lingual Multi-Cultural Norm Discovery from Conversations On-the-Fly

Yi R. Fung, Tuhin Chakrabarty, Hao Guo, Owen Rambow, Smaranda Muresan, Heng Ji Β· 2023

Knowledge of norms is needed to understand and reason about acceptable behavior in human communication and interactions across sociocultural scenarios.Most computational research on norms has focused on a single culture, and manually built datasets, from nonconversational settings.We address these limitations by proposing a new framework, NORMSAGE 1 , to automatically extract culturespecific norms from multi-lingual conversations.NORMSAGE uses GPT-3 prompting to 1) extract candidate norms directly from conversations and 2) provide explainable selfverification to ensure correctness and relevance.Comprehensive empirical results show the promise of our approach to extract highquality culture-aware norms from multi-lingual conversations (English and Chinese), across several quality metrics.Further, our relevance verification can be extended to assess the adherence and violation of any norm with respect to a conversation on-the-fly, along with textual explanation.NORMSAGE achieves an AUC of 94.6% in this grounding setup, with generated explanations matching human-written quality.𝐚) 𝐈𝐧𝐒𝐭𝐒𝐚π₯ πƒπ’π¬πœπ¨π―πžπ«π’š: 𝒅𝒗𝒓(β‹…) irrelevant contradict entail Correctness Verdict ( ! π‘ͺ 𝒗 ): Correctness Explanation ( ! π‘ͺ 𝒆 ): Yes, honesty is the foundation of trust, and strong family relationships are built on trust.

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