Triple
T25414084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KCOS |
E636780
|
entity |
| Predicate | associatedAirportMilitaryUse |
P34628
|
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: [KCOS, associatedAirportMilitaryUse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportMilitaryUse Context triple: [KCOS, associatedAirportMilitaryUse, yes]
-
A.
airportServesMilitaryTraffic
chosen
Indicates that the airport accommodates or handles military air traffic in addition to any other types of traffic.
-
B.
airfieldUsedDuring
Indicates that an airfield was in operational use during a specified time period or event.
-
C.
isCivilAirport
Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
-
D.
usedByMilitaryInstallations
Indicates that something is utilized or operated by military installations for their functions or activities.
-
E.
operatesAirbasesIn
Indicates that an entity manages, controls, or conducts operations at airbases located within a specified area or jurisdiction.
- 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_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 21, 2026, 1:55 p.m.