Triple

T32332220
Position Surface form Disambiguated ID Type / Status
Subject Department of Medicine (Philippine General Hospital) E826081 entity
Predicate hospitalTypeServed P30483 FINISHED
Object tertiary government 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: tertiary government hospital | Statement: [Department of Medicine (Philippine General Hospital), hospitalTypeServed, tertiary government hospital]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hospitalTypeServed
Context triple: [Department of Medicine (Philippine General Hospital), hospitalTypeServed, tertiary government hospital]
  • A. hasHospitalType chosen
    Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
  • B. hospitalLevel
    Indicates the classification or rank of a hospital within a defined healthcare system or hierarchy.
  • C. designatedAsFlagshipHospitalFor
    Indicates that one hospital has been officially selected or recognized as the primary or leading flagship institution for another entity (such as a health system, region, or organization).
  • D. hospitalLocation
    Indicates the geographic place or address where a hospital is situated.
  • E. healthcareType
    Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
  • 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_69f34913d9048190befaa634025232be completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bdf0d6988190bd745ece41f30661 completed May 3, 2026, 3:16 a.m.
PD Predicate disambiguation batch_69f6b633e0c88190a727bb7d2751e2d5 completed May 3, 2026, 2:43 a.m.
Created at: May 1, 2026, 12:47 a.m.