Triple
T8491615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A359 |
E200982
|
entity |
| Predicate | aircraftCabinLayout |
P16894
|
FINISHED |
| Object | twin-aisle |
—
|
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: twin-aisle | Statement: [A359, aircraftCabinLayout, twin-aisle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftCabinLayout Context triple: [A359, aircraftCabinLayout, twin-aisle]
-
A.
cabinConfiguration
chosen
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
B.
vehicleLayout
Indicates how the components or seating within a vehicle are arranged or configured relative to each other.
-
C.
isPartOfAirportLayout
Indicates that something is a component or element within the overall physical or functional layout of an airport.
-
D.
cockpitType
Indicates the specific configuration or style of cockpit associated with an entity (e.g., vehicle or aircraft).
-
E.
flightDeckType
Indicates the specific configuration or design type of a vehicle’s flight deck (cockpit/control area).
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe55af3f48190a8cd64cdce0ebd4c |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd107633c8190a36ba50e07876918 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:13 p.m.