Triple
T22422154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mitsubishi Regional Jet |
E554273
|
entity |
| Predicate | flightDeckTechnology |
P7133
|
FINISHED |
| Object | glass cockpit |
—
|
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: glass cockpit | Statement: [Mitsubishi Regional Jet, flightDeckTechnology, glass cockpit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flightDeckTechnology Context triple: [Mitsubishi Regional Jet, flightDeckTechnology, glass cockpit]
-
A.
flightDeckFeature
Indicates that one entity is a feature, component, or element that is part of or present on the flight deck of another entity.
-
B.
flightDeckType
Indicates the specific configuration or design type of a vehicle’s flight deck (cockpit/control area).
-
C.
cockpitType
Indicates the specific configuration or style of cockpit associated with an entity (e.g., vehicle or aircraft).
-
D.
flightDeckWidth
Indicates the measurement of how wide a vehicle’s flight deck is across its lateral (side-to-side) dimension.
-
E.
avionics
chosen
Indicates that an entity is related to the electronic systems used to control, monitor, or assist the operation of aircraft or spacecraft.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2a1a3c8190a649ee4df2429e69 |
completed | April 29, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
Created at: April 16, 2026, 8:47 p.m.