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OntologyAligner：用于生物医学本体规范化的本体对齐检索与层级引导大语言模型重排序
该 arXiv 预印本提出 OntologyAligner，一个结合本体对齐检索、大语言模型候选重排序和选择性层级引导精炼的三阶段框架，用于将自由文本映射到标准化生物医学本体概念。作者同时构建了 PhenoNormBench 基准，包含来自七个 Human Phenotype Ontology 数据集的 13,390 个样本。在 HPO 规范化任务上达到 88.78% Macro Top-1 和 86.75% Micro Top-1 准确率，分别超过最强基线 4.85 和 5.07 个百分点。消融实验显示三阶段均有互补贡献，敏感性分析表明在不同候选集规模和模型骨干下稳定，并在 MONDO、MEDIC、NCBITaxon 上验证了可移植性。
AI推荐理由 arXiv 预印本，方法描述具体，提出三阶段框架 OntologyAligner 并构建 PhenoNormBench 基准（13,390 样本），在 HPO 规范化上报告 88.78% Macro Top-1 与 86.75% Micro Top-1，较最强基线提升 4.85 和 5.07 个百分点，并验证了向 MONDO、MEDIC、NCBITaxon 的可移植性。属于生物医学本体规范化这一垂直领域的增量进展，对通用 AI 读者价值有限，且结果未经同行评审。
68
正文
Computer Science > Artificial Intelligence
arXiv:2609.10055 (cs)
[Submitted on 9 Sep 2026]
Title:OntologyAligner: Ontology-Aligned Retrieval and Hierarchy-Guided Large Language Model Reranking for Biomedical Ontology Normalization
Authors:Jie Song, Zhichuan Xu, Ziyu Lu, Meng Xiao, Cheng Bi, Yuxin Zhang, Xin Zheng, Xiaoran Li, Qiongfang Cao, Hao Yang, Bairong Shen
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Abstract:Biomedical ontology normalization maps free-text expressions to standardized concepts, enabling consistent integration and analysis of biomedical data. This task remains challenging because lexical variation and subtle distinctions among hierarchically related concepts can obscure concept boundaries. We present OntologyAligner, a three-stage framework that combines ontology-aligned retrieval, large language model candidate reranking, and selective hierarchy-guided refinement. We also construct PhenoNormBench, a unified benchmark comprising 13,390 samples from seven Human Phenotype Ontology datasets. OntologyAligner achieved state-of-the-art performance on HPO normalization, with 88.78% Macro Top-1 Accuracy and 86.75% Micro Top-1 Accuracy, exceeding the strongest baseline by 4.85 and 5.07 percentage points, respectively. Ablation analyses showed complementary contributions from all three stages, and sensitivity analyses demonstrated stability across candidate-set sizes and model backbones. Applications to MONDO, MEDIC, and NCBITaxon further established portability to other ontologies. OntologyAligner offers a generalizable framework for accurate mapping of biomedical text to structured ontology concepts. PhenoNormBench and the code are publicly available at this https URL.
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Subjects:
Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
Cite as:
arXiv:2609.10055 [cs.AI]
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arXiv:2609.10055v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2609.10055
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arXiv-issued DOI via DataCite (pending registration)
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From: Jie Song [view email]
[v1]
Wed, 9 Sep 2026 11:30:25 UTC (1,127 KB)
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