Triple
T27567334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolmogorov–Sinai entropy |
E695939
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | dynamical systems invariant |
C21648
|
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: dynamical systems invariant Context triple: [Kolmogorov–Sinai entropy, instanceOf, dynamical systems invariant]
-
A.
theory of dynamical systems
The theory of dynamical systems studies how points in a mathematical space evolve over time under repeated application of rules or equations, revealing patterns such as stability, chaos, and long-term behavior.
-
B.
tool in dynamical systems theory
chosen
A tool in dynamical systems theory is a conceptual or computational method—such as phase portraits, Lyapunov functions, or Poincaré maps—used to analyze, visualize, and understand the qualitative and quantitative behavior of dynamical systems over time.
-
C.
nonlinear dynamical system
A nonlinear dynamical system is a system whose evolution over time is governed by equations in which the change of state depends on the current state in a nonlinear way, often leading to complex behaviors such as bifurcations and chaos.
-
D.
classical invariant
A classical invariant is a quantity or property associated with a mathematical object that remains unchanged under a specified group of classical transformations, such as rotations, translations, or linear changes of coordinates.
-
E.
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.
- 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_69ef53891af88190a193c5e2a1dac9b1 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 27, 2026, 1:41 p.m.