Triple
T16249675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boltzmann–Kac equation |
E394467
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | mathematical model in statistical mechanics |
C3053
|
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: mathematical model in statistical mechanics Context triple: [Boltzmann–Kac equation, instanceOf, mathematical model in statistical mechanics]
-
A.
equation in statistical physics
chosen
An equation in statistical physics is a mathematical relation that connects microscopic properties of particles and their interactions to macroscopic thermodynamic quantities, enabling the prediction of a system’s collective behavior.
-
B.
statistical model
A statistical model is a mathematical representation of observed data and underlying random processes, used to describe relationships, make inferences, and generate predictions.
-
C.
generalization of the Ising model
A generalization of the Ising model is a statistical physics framework that extends the original spin-½ lattice system to more complex spins, interactions, geometries, or degrees of freedom to describe a wider range of phase transitions and critical phenomena.
-
D.
statistical ensemble
A statistical ensemble is a large collection of hypothetical copies of a system, each representing a possible microstate consistent with given macroscopic conditions, used to calculate average physical properties in statistical mechanics.
-
E.
theoretical model
A theoretical model is an abstract, simplified representation of a system or phenomenon used to explain, predict, or understand its behavior based on underlying principles and assumptions.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 10, 2026, 5:04 a.m.