Triple
T112203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voyager KC2 |
E2271
|
entity |
| Predicate | hasLandingGear |
P3545
|
FINISHED |
| Object | tricycle retractable landing gear |
—
|
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: tricycle retractable landing gear | Statement: [Voyager KC2, hasLandingGear, tricycle retractable landing gear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandingGear Context triple: [Voyager KC2, hasLandingGear, tricycle retractable landing gear]
-
A.
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.
-
B.
landingGearType
chosen
Indicates the specific kind or configuration of landing gear that an object (typically an aircraft or vehicle) uses.
-
C.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling system.
-
D.
hasGroundTransportation
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
-
E.
hasLiftType
Indicates the specific type or category of lift associated with an entity.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256425a488190959d71e39e699d90 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.