Triple
T5835904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edmonton City Centre Airport |
E129467
|
entity |
| Predicate | servedAircraftType |
P30181
|
FINISHED |
| Object | turboprop aircraft |
—
|
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: turboprop aircraft | Statement: [Edmonton City Centre Airport, servedAircraftType, turboprop aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedAircraftType Context triple: [Edmonton City Centre Airport, servedAircraftType, turboprop aircraft]
-
A.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
B.
usedByAircraftType
chosen
Indicates that something (such as equipment, infrastructure, or a procedure) is employed or operated by a specific type or category of aircraft.
-
C.
referredAircraftUsedFor
Indicates that the referenced aircraft is utilized for a particular purpose, role, or operation in relation to another entity or context.
-
D.
referredAircraftUsedIn
Indicates that an aircraft being referred to is the one that was actually used in a particular event, operation, or context.
-
E.
aircraftTypesCarried
Indicates that one entity (typically a vessel, facility, or platform) carries or is capable of carrying specific types of aircraft as part of its operations or configuration.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.