Triple
T25414082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KCOS |
E636780
|
entity |
| Predicate | associatedAirportOwnerType |
P169557
|
FINISHED |
| Object | public |
—
|
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: public | Statement: [KCOS, associatedAirportOwnerType, public]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportOwnerType Context triple: [KCOS, associatedAirportOwnerType, public]
-
A.
airportOwner
Indicates that one entity owns, controls, or holds primary legal responsibility for an airport.
-
B.
airportOwnershipModel
chosen
Indicates the type or structure of ownership or governance arrangement under which an airport is held or operated.
-
C.
associatedWithAirportType
Indicates that an entity has a connection or linkage to a specific category or type of airport.
-
D.
airlineOwnershipType
Indicates the type or nature of ownership relationship that exists between an airline and its owning entity.
-
E.
belongsToAirportOperator
Indicates that an airport or related facility is owned, managed, or operated by a specific airport operating organization.
- 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_69e75db4135881909acc287ebcb7a505 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: April 21, 2026, 1:55 p.m.