Narrative similarity is a challenging problem that requires reasoning over three aspects of narratives, including (1) the abstract theme; (2) the course of action and (3) the outcomes of narratives. We present UTD.HLTRISIM.NARRATIVES, our method developed for SemEval 2026 Task 4 (Narrative Story Similarity), which combines contrastive reasoning prompting with careful selection of few-shot examples to guide a Large Language Model(LLM) toward decisions of narrative comparative similarity. A curriculum learning framework orders examples of narrative triplets presented to the LLM by using a score that quantifies the impact of common narratives aspects with information discerned from several distractors of narrative similarity between pairs ofnarratives 1.