ArticleJournal of biomedical semantics2026
A practical and nuanced framework for entity linking evaluation.
Article in Journal of biomedical semantics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundEntity linking maps textual mentions with entities in vocabularies. While accuracy is the primary metric for entity linking evaluation, it fails to capture the complexity of model behaviour.
resultsWe propose an entity linking evaluation framework that clarifies the target objects of metrics calculation, incorporates term hierarchy, generates performance profiles, and summarises them as model characteristics. The framework emphasises hierarchical vocabulary structures, shifting the focus from text-level label matching to semantic comparison between concepts. We illustrate the competence and utility of this framework through a case study on disease entity linking.
conclusionOur results highlight the importance of aligning evaluation metrics with application-specific requirements, and provide structured hierarchical error analysis for entity linking, paving the way for more nuanced and practical assessments of entity linking systems.
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