Triple
T6036280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horizon Air |
E134428
|
entity |
| Predicate | aircraftCategoryOperated |
P62605
|
FINISHED |
| Object | turboprop |
—
|
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 | Statement: [Horizon Air, aircraftCategoryOperated, turboprop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftCategoryOperated Context triple: [Horizon Air, aircraftCategoryOperated, turboprop]
-
A.
typicalAircraftTypeCategory
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
-
B.
operatesAircraftBrand
Indicates that an entity actively uses or runs aircraft belonging to a specified brand in its operations.
-
C.
fleetTypeOperated
chosen
Indicates that an entity operates or manages a particular type or category of fleet.
-
D.
airlineFleetCategory
Indicates the classification category of an airline based on the characteristics or size of its aircraft fleet.
-
E.
historicalAircraftOperated
Indicates that an entity previously operated a specific aircraft model during a past period, but no longer does so.
- 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b4e3ec819089b2d119ea2953fe |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049e9a68c81909da0cfe4779ce9b5 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:08 p.m.