Triple
T24652274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KBIL |
E610282
|
entity |
| Predicate | supportsCommercialAirService |
P80333
|
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: [KBIL, supportsCommercialAirService, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCommercialAirService Context triple: [KBIL, supportsCommercialAirService, yes]
-
A.
supportsCommercialFlights
chosen
Indicates that the subject provides the necessary facilities, services, or conditions for regular commercial passenger or cargo flights to operate.
-
B.
hasNoRegularCommercialAirlineService
Indicates that a location or facility is not served by any scheduled, routine commercial airline flights.
-
C.
isCommercialServiceAirport
Indicates that an airport is designated and operated as a commercial service facility offering scheduled passenger or cargo air transport services.
-
D.
hasCommercialServices
Indicates that one entity provides or offers commercial services to another entity or within a specified context.
-
E.
servesAviationType
Indicates that one entity provides services or functions specifically for a particular type or category of aviation.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 2:34 a.m.