Triple
T19548967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macksville Ambulance Station |
E489148
|
entity |
| Predicate | typicalPatients |
P59096
|
FINISHED |
| Object | acutely ill persons |
—
|
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: acutely ill persons | Statement: [Macksville Ambulance Station, typicalPatients, acutely ill persons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPatients Context triple: [Macksville Ambulance Station, typicalPatients, acutely ill persons]
-
A.
primaryPatientType
chosen
Indicates the main category or classification of patient that is primarily associated with or targeted by an entity, action, or service.
-
B.
typicalAdmission
Indicates that an entity is a standard or commonly expected type of admission associated with another entity (such as an institution, event, or program).
-
C.
hasTypicalConditions
Indicates that something is associated with conditions or circumstances that are commonly or normally present for it.
-
D.
typicalMembers
Indicates that the related entities are representative or characteristic members of a larger group, category, or class.
-
E.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d2e5e588190ac3a6f612d4fb54b |
completed | April 20, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.