Triple
T25725542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milstein method |
E645106
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | numerical scheme for stochastic differential equations |
C7231
|
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: numerical scheme for stochastic differential equations Context triple: [Milstein method, instanceOf, numerical scheme for stochastic differential equations]
-
A.
numerical integration method for ordinary differential equations
A numerical integration method for ordinary differential equations is an algorithmic procedure that approximates the solution of an ODE over discrete steps by iteratively updating the dependent variable using information about its derivative.
-
B.
shock-capturing scheme
A shock-capturing scheme is a numerical method for solving hyperbolic partial differential equations that automatically resolves shock waves and discontinuities without explicitly tracking their locations, typically using conservative formulations and nonlinear limiters.
-
C.
time-stepping scheme
chosen
A time-stepping scheme is a numerical method that advances the solution of time-dependent equations from one discrete time level to the next.
-
D.
stochastic process
A stochastic process is a collection of random variables indexed by time or space that describes the evolution of a system subject to inherent randomness.
-
E.
method in differential equations
A method in differential equations is a systematic procedure or algorithm used to find exact or approximate solutions to equations involving unknown functions and their derivatives.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
Created at: April 21, 2026, 10:23 p.m.