Triple

T16447966
Position Surface form Disambiguated ID Type / Status
Subject Nishtar Medical University E399479 entity
Predicate hasTeachingHospitalStatus P30483 FINISHED
Object yes 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: yes | Statement: [Nishtar Medical University, hasTeachingHospitalStatus, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTeachingHospitalStatus
Context triple: [Nishtar Medical University, hasTeachingHospitalStatus, yes]
  • A. isTeachingHospitalFor
    Indicates that one institution serves as a clinical training site or educational facility for another, typically a medical school or health education program.
  • B. hasTeachingHospitalComplex
    Indicates that an entity is associated with or includes a complex of facilities functioning as a teaching hospital.
  • C. hasHospitalType chosen
    Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
  • D. servesAsPrimaryTeachingHospitalFor
    Indicates that one institution functions as the main clinical training and teaching site for another institution, typically a medical school or academic program.
  • E. 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.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32cddfc3c8190919b49f74b7e8e1a completed April 18, 2026, 7:03 a.m.
PD Predicate disambiguation batch_69e227048d608190a4205eae3117629a completed April 17, 2026, 12:26 p.m.
Created at: April 10, 2026, 5:10 a.m.