Triple
T112202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voyager KC2 |
E2271
|
entity |
| Predicate | hasWingConfiguration |
P7143
|
FINISHED |
| Object | low-wing monoplane |
—
|
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: low-wing monoplane | Statement: [Voyager KC2, hasWingConfiguration, low-wing monoplane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWingConfiguration Context triple: [Voyager KC2, hasWingConfiguration, low-wing monoplane]
-
A.
aircraftConfiguration
Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
-
B.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling system.
-
C.
landingGearType
Indicates the specific kind or configuration of landing gear that an object (typically an aircraft or vehicle) uses.
-
D.
hasLiftType
Indicates the specific type or category of lift associated with an entity.
-
E.
wingspan
Indicates the distance from the tip of one wing to the tip of the other wing when fully extended.
- 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_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. |
| PDg | Predicate description generation | batch_69a2587e598c81909e1082b813971f48 |
completed | Feb. 28, 2026, 2:52 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.