Triple
T1780829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbus A340 |
E39285
|
entity |
| Predicate | landingGearConfiguration |
P3545
|
FINISHED |
| Object | tricycle 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 landing gear | Statement: [Airbus A340, landingGearConfiguration, tricycle landing gear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landingGearConfiguration Context triple: [Airbus A340, landingGearConfiguration, tricycle landing gear]
-
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.
wingConfiguration
Indicates how the wings of an aircraft or creature are arranged or structured relative to its body and to each other.
-
D.
aircraftConfiguration
Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
-
E.
landingCapability
Indicates the ability or suitability of an entity (e.g., a vehicle or system) to perform a landing under specified conditions.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.