MedPath: Multi-Domain Cross-Vocabulary Hierarchical Paths for Biomedical Entity Linking
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866909901108805632 |
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| author | Mishra, Nishant Aziz, Wilker Calixto, Iacer |
| author_facet | Mishra, Nishant Aziz, Wilker Calixto, Iacer |
| contents | Progress in biomedical Named Entity Recognition (NER) and Entity Linking (EL) is currently hindered by a fragmented data landscape, a lack of resources for building explainable models, and the limitations of semantically-blind evaluation metrics. To address these challenges, we present MedPath, a large-scale and multi-domain biomedical EL dataset that builds upon nine existing expert-annotated EL datasets. In MedPath, all entities are 1) normalized using the latest version of the Unified Medical Language System (UMLS), 2) augmented with mappings to 62 other biomedical vocabularies and, crucially, 3) enriched with full ontological paths -- i.e., from general to specific -- in up to 11 biomedical vocabularies. MedPath directly enables new research frontiers in biomedical NLP, facilitating training and evaluation of semantic-rich and interpretable EL systems, and the development of the next generation of interoperable and explainable clinical NLP models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_10887 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MedPath: Multi-Domain Cross-Vocabulary Hierarchical Paths for Biomedical Entity Linking Mishra, Nishant Aziz, Wilker Calixto, Iacer Computation and Language Databases Progress in biomedical Named Entity Recognition (NER) and Entity Linking (EL) is currently hindered by a fragmented data landscape, a lack of resources for building explainable models, and the limitations of semantically-blind evaluation metrics. To address these challenges, we present MedPath, a large-scale and multi-domain biomedical EL dataset that builds upon nine existing expert-annotated EL datasets. In MedPath, all entities are 1) normalized using the latest version of the Unified Medical Language System (UMLS), 2) augmented with mappings to 62 other biomedical vocabularies and, crucially, 3) enriched with full ontological paths -- i.e., from general to specific -- in up to 11 biomedical vocabularies. MedPath directly enables new research frontiers in biomedical NLP, facilitating training and evaluation of semantic-rich and interpretable EL systems, and the development of the next generation of interoperable and explainable clinical NLP models. |
| title | MedPath: Multi-Domain Cross-Vocabulary Hierarchical Paths for Biomedical Entity Linking |
| topic | Computation and Language Databases |
| url | https://arxiv.org/abs/2511.10887 |