Triple
T15769168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nhulunbuy Regional Hospital |
E382303
|
entity |
| Predicate | healthcareSetting |
P90357
|
FINISHED |
| Object | acute 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: acute care | Statement: [Nhulunbuy Regional Hospital, healthcareSetting, acute care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthcareSetting Context triple: [Nhulunbuy Regional Hospital, healthcareSetting, acute care]
-
A.
clinicalSetting
chosen
Indicates that an action, observation, or interaction occurs within a healthcare or medical care environment.
-
B.
treatmentSetting
Indicates the type of environment or context in which a treatment or intervention is delivered.
-
C.
healthSystem
Indicates a relationship where an entity functions as, belongs to, or is managed within a particular health care system or network.
-
D.
healthcareType
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e051951bac8190a7d45f3612c6de72 |
completed | April 16, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.