Triple
T30209753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbus Broughton plant |
E768035
|
entity |
| Predicate | usesTransportAircraft |
P180251
|
FINISHED |
| Object | Airbus Beluga |
—
|
NE NERFINISHED |
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: Airbus Beluga | Statement: [Airbus Broughton plant, usesTransportAircraft, Airbus Beluga]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTransportAircraft Context triple: [Airbus Broughton plant, usesTransportAircraft, Airbus Beluga]
-
A.
usesCarrierAircraft
Indicates that one entity employs or operates aircraft that are designed to be launched from and recovered by an aircraft carrier.
-
B.
usesAircraftFeature
Indicates that one entity employs or takes advantage of a specific feature or capability of an aircraft.
-
C.
usesTransport
Indicates that an entity employs or relies on a particular mode or means of transportation to move from one place to another.
-
D.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
E.
aircraftRoleRequired
Indicates that a specific operational role or function is required of an aircraft within a given context or mission.
- 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_69f2247eb0848190b4032f302d39c0d9 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
| PDg | Predicate description generation | batch_69f739a58b3c81908abc2b8738a65678 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 29, 2026, 7:32 p.m.