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arXiv cs.AI ·
SAGE: A Hierarchical Framework for Evaluating Interpretive Literary Quality in Narratives
תקציר מקורי באנגליתarXiv:2609.06611v1 Announce Type: cross Abstract: Assessing the literary quality of narratives requires evaluating interpretive dimensions (cultural representation, emotional depth, and philosophical engagement) that existing NLG metrics cannot measure. We introduce SAGE, a six-layer evaluation framework that separates rule-based assessment of observable textual properties from LLM-based evaluation of interpretive qualities drawn from cultural theory, affect theory, and existentialist philosophy. Each interpretive layer is assessed through multi-round iterative LLM evaluation with independent cross-validation, achieving measurement-grade reliability (98.8% convergence, >94% inter-rater agreement) stable across evaluator models. Validated on 600 evaluations across 100 short stories, our cen
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