Triple
T18865002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bogoliubov transformation |
E461415
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | canonical transformation |
C3059
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: canonical transformation Context triple: [Bogoliubov transformation, instanceOf, canonical transformation]
-
A.
mathematical transformation
A mathematical transformation is a function or operation that systematically maps elements from one set or space to another, often altering their position, scale, orientation, or form while following defined rules.
-
B.
asymmetric transformation
An asymmetric transformation is a process or operation that changes an object, system, or data in a way that is not identical or easily reversible in the opposite direction, often producing different outcomes depending on the direction of application.
-
C.
coordinate transformation
chosen
A coordinate transformation is a mathematical operation that converts the representation of points or vectors from one coordinate system to another while preserving their underlying geometric relationships.
-
D.
integral of motion
An integral of motion is a physical quantity that remains constant along the trajectory of a dynamical system due to its underlying symmetries or conservation laws.
-
E.
generalization of Poisson bracket
A generalization of the Poisson bracket is a bilinear operation on functions (or observables) that extends the classical Poisson structure—often relaxing antisymmetry, the Jacobi identity, or locality—to encompass broader algebraic or geometric frameworks such as Nambu, Gerstenhaber, or higher/derived brackets.
- F. None of above.
Provenance (1 batch)
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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 10, 2026, 11:57 a.m.