Triple
T12502838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stefan problem |
E298871
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | partial differential equation model |
C3712
|
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: partial differential equation model Context triple: [Stefan problem, instanceOf, partial differential equation model]
-
A.
partial differential equation
chosen
A partial differential equation is an equation that relates the partial derivatives of an unknown multivariable function, describing how it changes with respect to several independent variables.
-
B.
result in partial differential equations
A result in partial differential equations is a proven statement or theorem that characterizes the existence, uniqueness, regularity, behavior, or qualitative properties of solutions to equations involving multivariable derivatives.
-
C.
variable-coefficient differential equation
A variable-coefficient differential equation is a differential equation in which the coefficients multiplying the unknown function and its derivatives depend on the independent variable(s) rather than being constant.
-
D.
physical model
A physical model is a tangible, scaled, or otherwise material representation of an object, system, or phenomenon used to study, demonstrate, or predict its real-world behavior.
-
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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
Created at: April 8, 2026, 9:57 p.m.