Triple
T13965894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wyong Hospital |
E335920
|
entity |
| Predicate | isAcuteCareHospital |
P77960
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Wyong Hospital, isAcuteCareHospital, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAcuteCareHospital Context triple: [Wyong Hospital, isAcuteCareHospital, true]
-
A.
isAcuteCareFacility
chosen
Indicates that the entity functions as a healthcare facility providing short-term, intensive medical treatment for patients with severe or urgent conditions.
-
B.
isPublicHospital
Indicates that a hospital is owned, funded, or operated by a government or public authority rather than by private entities.
-
C.
hasHospitalType
Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
-
D.
containsHospital
Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
-
E.
isTeachingHospitalFor
Indicates that one institution serves as a clinical training site or educational facility for another, typically a medical school or health education program.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8c9e988190a84c9ca8a78b515f |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.