Triple

T2291849
Position Surface form Disambiguated ID Type / Status
Subject Maidashi Campus E51520 entity
Predicate hasTypeOfHospital 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: [Maidashi Campus, hasTypeOfHospital, university hospital]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTypeOfHospital
Context triple: [Maidashi Campus, hasTypeOfHospital, university hospital]
  • A. hasHospitalType chosen
    Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
  • B. isPublicHospital
    Indicates that a hospital is owned, funded, or operated by a government or public authority rather than by private entities.
  • C. 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.
  • D. isTeachingHospitalFor
    Indicates that one institution serves as a clinical training site or educational facility for another, typically a medical school or health education program.
  • E. hasResearchHospital
    Indicates that an entity possesses, is associated with, or operates a hospital facility dedicated to conducting medical or clinical research.
  • 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_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abcd0e42248190ada33b84d75caa64 completed March 7, 2026, 7 a.m.
PD Predicate disambiguation batch_69abc589295c819092989820c2b4e9d8 completed March 7, 2026, 6:28 a.m.
Created at: March 4, 2026, 7:48 p.m.