Triple
T13128979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marina Municipal Airport |
E311916
|
entity |
| Predicate | servesTypeOfAircraft |
P71775
|
FINISHED |
| Object | small aircraft |
—
|
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: small aircraft | Statement: [Marina Municipal Airport, servesTypeOfAircraft, small aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesTypeOfAircraft Context triple: [Marina Municipal Airport, servesTypeOfAircraft, small aircraft]
-
A.
servesAviationType
chosen
Indicates that one entity provides services or functions specifically for a particular type or category of aviation.
-
B.
supportsAircraft
Indicates that one entity is capable of accommodating, carrying, or enabling the operation of an aircraft.
-
C.
aircraftRoleSupported
Indicates that a given role or function is supported or enabled for a particular aircraft.
-
D.
usedByAircraftType
Indicates that something (such as equipment, infrastructure, or a procedure) is employed or operated by a specific type or category of aircraft.
-
E.
aircraftTypesUsedOn
Indicates the types or models of aircraft that are used on or assigned to a particular route, service, operation, or context.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819bfd348190a22d44f837877e1c |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:07 p.m.