Triple
T23884921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kearney Regional Airport |
E600302
|
entity |
| Predicate | hasRentalCarServices |
P6090
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kearney Regional Airport, hasRentalCarServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRentalCarServices Context triple: [Kearney Regional Airport, hasRentalCarServices, yes]
-
A.
hasRentalCarCenter
chosen
Indicates that a location or facility includes or is associated with a rental car center where vehicles can be rented.
-
B.
hasCartRental
Indicates that an entity provides or is associated with the service of renting carts to another entity.
-
C.
hasFuelServices
Indicates that one entity provides or is equipped with fuel-related services or facilities for another entity.
-
D.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
E.
hasDrivingCabs
Indicates that an entity (such as a vehicle or train) is equipped with one or more driving cabs from which it can be operated or controlled.
- 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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ccfd99d481908aae44b387853c7d |
completed | April 29, 2026, 9:18 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:24 p.m.