Datasets like SQuAD and Natural Questions focus on extractive QA. CoQA focuses on conversational history. While datasets like e-SNLI exist for natural language inference, a large-scale, general-domain QA dataset focusing on explicit justification remains scarce.
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We employed a "gold-standard" validation set where a subset of 1,000 samples was reviewed by domain experts. Inter-annotator agreement (Cohen’s Kappa) for justification quality was measured at 0.82, indicating high reliability. Pro tip: Bulk orders (10+ units) often qualify