Triple
T6344847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunter Army Airfield |
E142716
|
entity |
| Predicate | supportsAircraft |
P70100
|
FINISHED |
| Object | fixed-wing 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: fixed-wing aircraft | Statement: [Hunter Army Airfield, supportsAircraft, fixed-wing aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsAircraft Context triple: [Hunter Army Airfield, supportsAircraft, fixed-wing aircraft]
-
A.
runwaySupportsAircraftType
Indicates that a particular runway is suitable and certified for use by a specified type of aircraft.
-
B.
aircraftRoleSupported
Indicates that a given role or function is supported or enabled for a particular aircraft.
-
C.
usesCarrierAircraft
Indicates that one entity employs or operates aircraft that are designed to be launched from and recovered by an aircraft carrier.
-
D.
supportsNarrowBodyAircraft
Indicates that one entity is capable of accommodating, servicing, or being compatible with narrow-body aircraft.
-
E.
supportsWideBodyAircraft
Indicates that an entity (such as an airport, runway, or gate) is capable of accommodating and handling wide-body aircraft operations.
- F. None of above. chosen
Provenance (4 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067b7e0d08190abacaf41c08ed15e |
completed | March 22, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:31 p.m.