Triple

T3826120
Position Surface form Disambiguated ID Type / Status
Subject Department of Oncology, University Hospital Zurich E88693 entity
Predicate typeOfHospitalCare P30483 FINISHED
Object tertiary care LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: tertiary care | Statement: [Department of Oncology, University Hospital Zurich, typeOfHospitalCare, tertiary care]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfHospitalCare
Context triple: [Department of Oncology, University Hospital Zurich, typeOfHospitalCare, tertiary care]
  • A. hasHospitalType chosen
    Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
  • B. healthcareType
    Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
  • C. containsHospital
    Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
  • D. isPublicHospital
    Indicates that a hospital is owned, funded, or operated by a government or public authority rather than by private entities.
  • E. majorHospital
    Indicates that a hospital holds a primary or leading status within a healthcare system or region, typically due to its size, capacity, or range of services.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69aed9538cf881909d9ce8ca4ac7c18c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeeb8459f881908a2c91bb07e381ef completed March 9, 2026, 3:47 p.m.
PD Predicate disambiguation batch_69aee74c2e04819094b94b3c0bac1806 completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:17 p.m.