Adapting Clinical Event Annotation to Dutch Primary Care: An Event Annotation Framework for Post-Acute Infection Syndromes

Extracting clinical information from Dutch free-text medical notes requires language-specific annotation resources, yet Dutch primary care lacks a reusable event-annotation framework for infections, post-acute infection syndromes (PAIS), and related symptoms. We adapted the COVID-19 Annotated Clinical Text (CACT) framework to Dutch and applied it to GP notes for PAIS event extraction. The framework has three annotation layers: a D iagnostic E xpression typology covering acute infections, post-acute syndromes, and relevant comorbidities; an eleven-subtype E vidence inventory grounded in Dutch primary-care testing practice; and explicit decision rules for the SOEP structure of Dutch general practitioner (GP) notes (Subjective, Objective, Evaluation, Plan), including the distinction between clinician hedging and patient-side hypotheticals. On a 200-note pilot, span-level F ₁ under the Lybarger criterion reached 0.51 [95% CI: 0.47– 0.55] across six core entities; restricted to spans both annotators noticed, conditional F ₁ reached 0.78 [0.75–0.80], indicating that most disagreement stems from annotation coverage rather than label assignment. The adaptation illustrates how an English event-based clinical annotation framework can be extended to a new language and clinical setting, yielding a reusable resource for Dutch clinical NLP; which steps generalise beyond this case (CACT to Dutch primary care) and which are specific to Dutch or PAIS remain to be tested.