Triple
T9888542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Metropolitan public hospitals |
E181396
|
entity |
| Predicate | typeOfCareFocus |
P7500
|
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: [Tokyo Metropolitan public hospitals, typeOfCareFocus, tertiary care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCareFocus Context triple: [Tokyo Metropolitan public hospitals, typeOfCareFocus, tertiary care]
-
A.
focusesOnMedicalCare
Indicates that one entity directs attention, resources, or activity specifically toward providing or improving medical care for another entity.
-
B.
healthcareType
chosen
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
C.
primaryPatientType
Indicates the main category or classification of patient that is primarily associated with or targeted by an entity, action, or service.
-
D.
requiresCare
Indicates that one entity depends on another to provide care, attention, or maintenance for its proper functioning or well-being.
-
E.
providesCareSetting
Indicates that one entity serves as the care environment or setting in which another entity receives or delivers care.
- 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4592db881909b134834dde614d8 |
completed | April 2, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69cd1d810ed48190a252b70e9390c8f3 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:39 p.m.