Triple
T7496898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pacific Western Airlines |
E177152
|
entity |
| Predicate | operatedAircraftCategory |
P45618
|
FINISHED |
| Object | jet airliners |
—
|
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: jet airliners | Statement: [Pacific Western Airlines, operatedAircraftCategory, jet airliners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedAircraftCategory Context triple: [Pacific Western Airlines, operatedAircraftCategory, jet airliners]
-
A.
typicalAircraftTypeCategory
chosen
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
-
B.
aircraftRoleOperated
Indicates that an entity operates or has operated in a specified role or function within the context of aircraft operations.
-
C.
airworthinessCategory
Indicates the regulatory airworthiness classification assigned to an aircraft or component, defining the standards and conditions under which it is approved to operate.
-
D.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
airlineFleetCategory
Indicates the classification category of an airline based on the characteristics or size of its aircraft fleet.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81b431481908214b69c6c8d83bc |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d266d88190982cf5d2ee2e9564 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:44 p.m.