Triple
T2956527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bowling Green–Warren County Regional Airport |
E79942
|
entity |
| Predicate | hasCommercialFlights |
P18239
|
FINISHED |
| Object | limited |
—
|
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: limited | Statement: [Bowling Green–Warren County Regional Airport, hasCommercialFlights, limited]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialFlights Context triple: [Bowling Green–Warren County Regional Airport, hasCommercialFlights, limited]
-
A.
hasDomesticFlights
Indicates that an airline or airport operates flights within the same country, connecting domestic destinations.
-
B.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
-
C.
operatesFlightsTo
Indicates that one entity (typically an airline) runs or provides flight services to the location represented by the other entity.
-
D.
hasTypeOfFlights
chosen
Indicates that an entity offers, includes, or is associated with specific categories or kinds of flights.
-
E.
hasScheduledFlights
Indicates that there are one or more flights planned and set to occur between the related entities according to a schedule.
- 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad992998f08190ac9428310983172e |
completed | March 8, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69ad960c5c8881909d679912bd7d78f3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:57 p.m.