Triple

T14292828
Position Surface form Disambiguated ID Type / Status
Subject Jikei University School of Medicine E354357 entity
Predicate hasAffiliatedHospitalType P30483 FINISHED
Object university hospital 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: university hospital | Statement: [Jikei University School of Medicine, hasAffiliatedHospitalType, university hospital]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAffiliatedHospitalType
Context triple: [Jikei University School of Medicine, hasAffiliatedHospitalType, university hospital]
  • A. hasAffiliatedHospital
    Indicates that one entity (typically a medical professional, clinic, or organization) is formally connected or associated with a particular hospital for professional or operational purposes.
  • B. hasHospitalType chosen
    Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
  • C. isAffiliatedHospitalNumber
    Indicates that a specific hospital is associated with or identified by a particular affiliation number within a healthcare or organizational system.
  • D. containsHospital
    Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
  • E. hasTeachingHospitalComplex
    Indicates that an entity is associated with or includes a complex of facilities functioning as a teaching hospital.
  • 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_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de7179368081908117a9ccfbf94fd4 completed April 14, 2026, 4:55 p.m.
PD Predicate disambiguation batch_69de2a8f81f08190af737e1654847aa6 completed April 14, 2026, 11:52 a.m.
Created at: April 10, 2026, 1:11 a.m.