Triple

T755094
Position Surface form Disambiguated ID Type / Status
Subject University Hospital Zurich E15535 entity
Predicate hasNursingStaffApprox P17907 FINISHED
Object 2500 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: 2500 | Statement: [University Hospital Zurich, hasNursingStaffApprox, 2500]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNursingStaffApprox
Context triple: [University Hospital Zurich, hasNursingStaffApprox, 2500]
  • A. employsApproximateNumberOfPeople chosen
    Indicates that an entity employs a roughly estimated or approximate number of people, rather than an exact headcount.
  • B. employedApproximately
    Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
  • C. staffIncluded
    Indicates that staff members are included or provided as part of the associated entity, service, or arrangement.
  • D. hasNearbyFacility
    Indicates that one entity is located close to or in the vicinity of a particular facility.
  • E. providesCareSetting
    Indicates that one entity serves as the care environment or setting in which another entity receives or delivers care.
  • 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a66820548190b373deb117187c2c completed March 1, 2026, 8:49 p.m.
PD Predicate disambiguation batch_69a4a501c4cc81908de6d63e3d4f60d7 completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:37 p.m.