Triple
T5834519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing C-32 |
E129434
|
entity |
| Predicate | C-32BRole |
P67455
|
FINISHED |
| Object | special operations transport |
—
|
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: special operations transport | Statement: [Boeing C-32, C-32BRole, special operations transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: C-32BRole Context triple: [Boeing C-32, C-32BRole, special operations transport]
-
A.
typeOfRebel
Indicates that one entity is a rebel belonging to, or classified under, a particular type or category of rebellion.
-
B.
intendedCrewVehicle
Indicates that a particular vehicle is designated or planned to be used by a specific crew.
-
C.
crewVariantName
Indicates the specific name or label assigned to a particular variant or version of a crew configuration.
-
D.
madeTheKesselRunIn
Indicates that an entity completed the Kessel Run within a specified amount of time or distance.
-
E.
commanderOnBoard
Indicates that a specific individual holds the role of commanding officer on a particular vehicle, vessel, or craft during its operation.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69c044a9c4f0819081b8c196932883f6 |
completed | March 22, 2026, 7:36 p.m. |
Created at: March 22, 2026, 3:54 p.m.