Triple
T6236575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laplace equation |
E139492
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | elliptic 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: elliptic partial differential equation Context triple: [Laplace equation, instanceOf, elliptic 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.
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).
-
C.
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.
-
D.
evolution equation
An evolution equation is a mathematical expression, typically a differential or integral equation, that describes how a system’s state changes over time according to specified dynamical rules.
-
E.
Green’s function in Euclidean space
A Green’s function in Euclidean space is a fundamental solution to a linear differential operator that represents the response at one point due to a unit source located at another point, enabling the construction of solutions to boundary value problems via superposition.
- 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
Created at: March 22, 2026, 4:23 p.m.