Triple
T28977073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VJC |
E734438
|
entity |
| Predicate | associatedAirlineHubCountry |
—
|
GENERATED |
| Object | Vietnam |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirlineHubCountry Context triple: [VJC, associatedAirlineHubCountry, Vietnam]
-
A.
linkedAirlineCountry
chosen
Indicates that there is an association between an airline and a country, such as the country where the airline is based, registered, or primarily operates.
-
B.
associatedAirportPrimaryHubFor
Indicates that an airport serves as the primary hub for a particular airline or transportation operator.
-
C.
associatedAirportOperatorCountry
Indicates the country in which the operator of the associated airport is based or registered.
-
D.
associatedAirlineHeadquartersIsland
Indicates that an airline’s headquarters are located on a specific island.
-
E.
associatedAirlinePrimaryMarket
Indicates that an airline is primarily associated with, or operates chiefly within, a particular geographic or commercial market.
- F. None of above.
Provenance (1 batch)
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_69f05b0d1e7c819092baab93d3fe277e |
completed | April 28, 2026, 7 a.m. |
Created at: April 28, 2026, 9:09 a.m.