Triple
T36836302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steklov eigenvalue problem |
E910281
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | spectral boundary value problem |
C41097
|
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: spectral boundary value problem Context triple: [Steklov eigenvalue problem, instanceOf, spectral boundary value problem]
-
A.
boundary value problem
chosen
A boundary value problem is a mathematical problem in which a differential equation is solved subject to specified conditions (boundary values) imposed on the solution at the boundaries of the domain.
-
B.
differential equation with singular potential
A differential equation with singular potential is an equation in which the coefficient representing the potential term becomes unbounded or undefined at certain points, leading to singular behavior in the solutions.
-
C.
free boundary problem
A free boundary problem is a type of mathematical or physical problem in which the shape or position of the boundary of the domain is not known in advance and must be determined as part of the solution.
-
D.
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.
-
E.
PDE inverse problem
A PDE inverse problem is the task of determining unknown parameters, inputs, or structures in a system governed by partial differential equations from indirect, often noisy, observational data.
- 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_69f76e7e9d60819092442fba73290a46 |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:13 p.m.