Triple
T17529834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curtiss P-36 Hawk |
E426898
|
entity |
| Predicate | tailwheelType |
P3545
|
FINISHED |
| Object | conventional tailwheel |
—
|
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 tailwheel | Statement: [Curtiss P-36 Hawk, tailwheelType, conventional tailwheel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tailwheelType Context triple: [Curtiss P-36 Hawk, tailwheelType, conventional tailwheel]
-
A.
landingGearType
chosen
Indicates the specific kind or configuration of landing gear that an object (typically an aircraft or vehicle) uses.
-
B.
landingGear
Indicates that an entity’s landing gear is present, deployed, or otherwise involved in a landing-related state or action relative to another entity or context.
-
C.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
D.
tailRotorConfiguration
Indicates the specific arrangement or design setup of a vehicle’s tail rotor relative to its main structure or propulsion system.
-
E.
typeOfAviation
Indicates the specific category or kind of aviation to which an entity belongs (e.g., commercial, military, private).
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45367d68c819097f300381322f11d |
completed | April 19, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.