Triple
T25430876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FUN |
E637248
|
entity |
| Predicate | airportSupportsAidFlights |
P38514
|
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: [FUN, airportSupportsAidFlights, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportSupportsAidFlights Context triple: [FUN, airportSupportsAidFlights, yes]
-
A.
hasAirportAccessTo
Indicates that one location or entity has direct access to another via an airport connection or service.
-
B.
airportUse
chosen
Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
-
C.
airSupport
Indicates that one entity provides aerial assistance or backing to another, typically through aircraft-based protection, transport, or attack.
-
D.
appliesToAirport
Indicates that something is relevant, valid, or specifically intended for use at a particular airport.
-
E.
servesFlightsTo
Indicates that one transportation provider regularly operates flights to a specified destination location.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 21, 2026, 1:58 p.m.