Triple
T32030640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calderón problem in inverse conductivity |
E817947
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | PDE inverse problem |
C57626
|
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: PDE inverse problem Context triple: [Calderón problem in inverse conductivity, instanceOf, PDE inverse problem]
-
A.
partial differential equation
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.
integro-differential equations
Integro-differential equations are mathematical equations that involve both integrals and derivatives of an unknown function, capturing systems where current rates of change depend on accumulated past behavior.
-
C.
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.
-
D.
initial value problem
An initial value problem is a type of differential equation together with specified values of the unknown function (and possibly its derivatives) at a starting point, from which a unique solution is sought.
-
E.
integral equation
An integral equation is a mathematical relation in which an unknown function appears under an integral sign, often equated to a given function, and must be solved over a specified domain.
- F. None of above. chosen
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_69f348fbc8148190b3c0f95d4772b153 |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:18 a.m.