Triple
T13271503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokosuka MXY8 Akigusa |
E316068
|
entity |
| Predicate | aircraftControlType |
P109258
|
FINISHED |
| Object | conventional aerodynamic controls |
—
|
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: conventional aerodynamic controls | Statement: [Yokosuka MXY8 Akigusa, aircraftControlType, conventional aerodynamic controls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftControlType Context triple: [Yokosuka MXY8 Akigusa, aircraftControlType, conventional aerodynamic controls]
-
A.
controlsPhaseOfFlight
Indicates that one entity has authority over or manages a specific phase of another entity’s flight operation.
-
B.
cockpitType
Indicates the specific configuration or style of cockpit associated with an entity (e.g., vehicle or aircraft).
-
C.
aircraftCommanded
Indicates that one entity serves as the commanding officer or leader in charge of operating, directing, or overseeing the other entity, which is an aircraft.
-
D.
flightDeckType
Indicates the specific configuration or design type of a vehicle’s flight deck (cockpit/control area).
-
E.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:26 p.m.