Triple
T36704152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potts glass |
E906309
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | generalization of the Potts model |
C29217
|
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: generalization of the Potts model Context triple: [Potts glass, instanceOf, generalization of the Potts model]
-
A.
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.
-
B.
spin model
chosen
A spin model is a mathematical representation of interacting discrete magnetic moments (spins) on a lattice or graph, used to study phase transitions and collective behavior in statistical and condensed matter physics.
-
C.
model in complex systems
A model in complex systems is a simplified, often computational or mathematical representation of interacting components whose collective behavior exhibits emergent, nonlinear, and adaptive dynamics that cannot be easily inferred from the properties of individual parts.
-
D.
model of irreversibility
A model of irreversibility is a conceptual framework that represents processes or systems whose evolution cannot be exactly reversed, typically due to entropy increase, information loss, or path-dependent dynamics.
-
E.
mechanism in statistical physics
A mechanism in statistical physics is a fundamental process or interaction rule at the microscopic level that gives rise to observed macroscopic statistical behaviors and emergent phenomena.
- 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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:12 p.m.