Triple

T1618718
Position Surface form Disambiguated ID Type / Status
Subject Johns Hopkins Bayview Medical Center E34781 entity
Predicate hasHospitalType P30483 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: [Johns Hopkins Bayview Medical Center, hasHospitalType, tertiary care]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasHospitalType
Context triple: [Johns Hopkins Bayview Medical Center, hasHospitalType, tertiary care]
  • A. isPublicHospital
    Indicates that a hospital is owned, funded, or operated by a government or public authority rather than by private entities.
  • B. 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.
  • C. hospitalizedIn
    Indicates that a person or patient is admitted for medical care and staying as an inpatient in a specified hospital or healthcare facility.
  • D. hasMedicalCenter
    Indicates that an entity possesses, hosts, or is associated with a medical center facility.
  • 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. chosen

Provenance (4 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a93fef600c819080fe75c42c8e6dac completed March 5, 2026, 8:33 a.m.
PD Predicate disambiguation batch_69a907c52a548190b648a31ea306dd5b completed March 5, 2026, 4:34 a.m.
PDg Predicate description generation batch_69a93fedcb108190ad91f938d5eeaaa2 completed March 5, 2026, 8:33 a.m.
Created at: March 4, 2026, 7:28 p.m.