Triple

T16761177
Position Surface form Disambiguated ID Type / Status
Subject Medical Center E407345 entity
Predicate hasMedicalConsultant P40116 FINISHED
Object physicians employed as advisors 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: physicians employed as advisors | Statement: [Medical Center, hasMedicalConsultant, physicians employed as advisors]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMedicalConsultant
Context triple: [Medical Center, hasMedicalConsultant, physicians employed as advisors]
  • A. consultsOn
    Indicates that one entity provides expert advice, guidance, or professional input to another entity regarding a specific subject, project, or decision.
  • B. hasDoctorActor
    Indicates that a doctor participates as an acting agent in the specified event or relationship.
  • C. requiresConsultationWith
    Indicates that performing an action or making a decision depends on first obtaining input, approval, or advice from a specified party.
  • D. publicConsultationHeld
    Indicates that a formal public consultation process has been conducted regarding a particular decision, policy, or project.
  • E. hasHealthcareProvider chosen
    Indicates that one entity receives healthcare services or medical oversight from another entity acting as its healthcare provider.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3abed67f88190afb1d392ff01a5e7 completed April 18, 2026, 4:06 p.m.
PD Predicate disambiguation batch_69e319cbd79c8190a03587a61c18bec0 completed April 18, 2026, 5:42 a.m.
Created at: April 10, 2026, 5:21 a.m.