Triple
T28361817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KNYL |
E718380
|
entity |
| Predicate | supportsFixedWingAircraft |
P70100
|
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: [KNYL, supportsFixedWingAircraft, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFixedWingAircraft Context triple: [KNYL, supportsFixedWingAircraft, yes]
-
A.
isFixedWing
Indicates that the subject is an aircraft that uses fixed, non-flapping wings to generate lift rather than rotating or flapping components.
-
B.
primaryFixedWingAircraft
Indicates that the subject is the main or principal fixed-wing aircraft associated with the given entity.
-
C.
supportsAircraft
chosen
Indicates that one entity is capable of accommodating, carrying, or enabling the operation of an aircraft.
-
D.
supportsSingleEngineAircraft
Indicates that the subject is designed, equipped, or authorized to accommodate or be compatible with single-engine aircraft.
-
E.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
- 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_69eff6ed5af48190be4e0adf298223e0 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_6a008e29f76881908e656dbbd7fceea3 |
completed | May 10, 2026, 1:54 p.m. |
| PD | Predicate disambiguation | batch_6a008dc01b308190bc26e69814692f82 |
completed | May 10, 2026, 1:53 p.m. |
Created at: April 28, 2026, 12:52 a.m.