Triple

T13974748
Position Surface form Disambiguated ID Type / Status
Subject Abubakar Tafawa Balewa University Teaching Hospital E336156 entity
Predicate hasLevelOfCare P98032 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: [Abubakar Tafawa Balewa University Teaching Hospital, hasLevelOfCare, tertiary care]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLevelOfCare
Context triple: [Abubakar Tafawa Balewa University Teaching Hospital, hasLevelOfCare, tertiary care]
  • A. hasFacilityLevel chosen
    Indicates the degree or tier of capability, service, or infrastructure that a particular facility possesses.
  • B. hasEmergencyCare
    Indicates that an entity provides or is equipped with emergency medical care services for another entity or individuals.
  • C. requiresCare
    Indicates that one entity depends on another to provide care, attention, or maintenance for its proper functioning or well-being.
  • D. eligibilityLevel
    Indicates the degree or tier of qualification an entity has for a given benefit, service, or status.
  • E. isAcuteCareFacility
    Indicates that the entity functions as a healthcare facility providing short-term, intensive medical treatment for patients with severe or urgent conditions.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e8fd6d48190a157eae8df3a2f3a completed April 14, 2026, 12:09 p.m.
PD Predicate disambiguation batch_69dd465a21408190b912a42c50ffa0d9 completed April 13, 2026, 7:39 p.m.
Created at: April 9, 2026, 10:18 p.m.