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HausaNLP at SemEval-2026 Task 7: A Locale-Conditional, Multi-Model Prompting Pipeline for Hausa Cultural Question Answering
Error analysis shows that a non-trivial fraction of failures are placeholder strings caused by API errors rather than incorrect generations, and that surface-level mismatches (verbosity, ortho-graphic variation) account for many of the remaining errors.
Team HausaNLP at SemEval-2026 Task 4: Narratives via Semantic Embeddings
A systematic ablation comparing five approaches to identify the more narratively similar of two candidate stories relative to an anchor identifies five systematic failure categories, distinct from the All Correct / Partial cases, including 23 Lexical Trap cases, 23 Hard Cases, and 24 Proposed-Recovery cases.