Triple
T8630955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A3ST |
E204399
|
entity |
| Predicate | aircraftSpecialization |
P51088
|
FINISHED |
| Object | outsize cargo logistics within Airbus production network |
—
|
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: outsize cargo logistics within Airbus production network | Statement: [A3ST, aircraftSpecialization, outsize cargo logistics within Airbus production network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftSpecialization Context triple: [A3ST, aircraftSpecialization, outsize cargo logistics within Airbus production network]
-
A.
aircraftRoleSupported
Indicates that a given role or function is supported or enabled for a particular aircraft.
-
B.
notableAircraftRole
Indicates that an aircraft is notably associated with performing a particular role or function.
-
C.
aircraftCapability
chosen
Indicates that an aircraft possesses a particular capability, function, or operational feature.
-
D.
primaryAircraftRole
Indicates the main operational function or mission type an aircraft is primarily designed or used to perform.
-
E.
typicalAircraftTypeCategory
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:27 p.m.