Triple
T22600973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cahn–Hilliard equation |
E574814
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | fourth-order partial differential equation |
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: fourth-order partial differential equation Context triple: [Cahn–Hilliard equation, instanceOf, fourth-order partial differential equation]
-
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.
fully nonlinear equation
A fully nonlinear equation is a differential equation in which the highest-order derivatives appear in a genuinely nonlinear way, not just linearly or as coefficients of lower-order terms.
-
D.
equation in the calculus of variations
An equation in the calculus of variations is a mathematical relation, typically an Euler–Lagrange equation, that characterizes the functions making a given functional stationary (usually minimizing or maximizing its value).
-
E.
elliptic differential operator
An elliptic differential operator is a linear differential operator whose principal symbol is invertible away from the zero section, ensuring strong regularity and smoothing properties for its solutions.
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
Created at: April 17, 2026, 2:50 p.m.