Triple
T37526867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Ambulance Service (Ghana) |
E932929
|
entity |
| Predicate | hasAmbulanceType |
P64826
|
FINISHED |
| Object | road ambulance |
—
|
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: road ambulance | Statement: [National Ambulance Service (Ghana), hasAmbulanceType, road ambulance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmbulanceType Context triple: [National Ambulance Service (Ghana), hasAmbulanceType, road ambulance]
-
A.
hasEmergencyTransport
chosen
Indicates that an entity provides, is equipped with, or has access to emergency transportation services or vehicles.
-
B.
hasTypeOfApparatus
Indicates that one entity is associated with, or utilizes, a specific kind or category of apparatus.
-
C.
hasCabType
Indicates that an entity is associated with or characterized by a specific type or category of cab.
-
D.
typeOfEmergencyService
Indicates the specific category or kind of emergency service associated with or provided in a given situation.
-
E.
hasCriticalApparatus
Indicates that a text or document is accompanied by a critical apparatus, i.e., scholarly notes, variant readings, and editorial commentary that analyze and support the main content.
- 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_69f76ec8862c8190bfa24145f5480642 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.