Triple
T21226486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nudm |
E523095
|
entity |
| Predicate | operatesAtPlane |
P143286
|
FINISHED |
| Object | Control plane |
—
|
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: Control plane | Statement: [Nudm, operatesAtPlane, Control plane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesAtPlane Context triple: [Nudm, operatesAtPlane, Control plane]
-
A.
locationOnAircraft
Indicates that one entity is physically situated on or within an aircraft.
-
B.
basedOnAircraft
Indicates that one entity is derived from, modeled after, or otherwise uses a particular aircraft as its basis or primary reference.
-
C.
aircraftOperationType
Indicates the specific manner or purpose for which an aircraft is being operated (e.g., commercial, private, military, training).
-
D.
operatorOfReferencedAircraft
Indicates that one entity serves as the operator (e.g., managing or controlling party) of an aircraft that is referenced elsewhere in the context.
-
E.
theaterOfUseOfAircraft
Indicates the geographic or operational area in which an aircraft is intended to be or is actually employed.
- 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_69e0b512ad94819087942b2ed925185f |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734ab3f6c819083e277ea1c33134e |
completed | April 21, 2026, 8:26 a.m. |
| PD | Predicate disambiguation | batch_69e5f60e1a888190ba75e2e900270a4e |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f993240c8190847c0b08e65726c8 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 3:44 p.m.