Triple
T22925592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jury stability table |
E569296
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | discrete-time stability test |
C22988
|
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: discrete-time stability test Context triple: [Jury stability table, instanceOf, discrete-time stability test]
-
A.
numerical stability condition
A numerical stability condition is a mathematical requirement on the step size, discretization parameters, or algorithmic choices that ensures errors in a numerical method do not grow uncontrollably during computation.
-
B.
stability concept in functional equations
A stability concept in functional equations studies how small deviations from an exact functional relationship affect the existence and form of nearby exact solutions, typically quantifying when approximate solutions imply true solutions close in some specified sense.
-
C.
fluctuation test
A fluctuation test is an experimental method used to determine whether mutations arise spontaneously and randomly or are induced by selective conditions, typically by analyzing variation in mutant counts across parallel cultures.
-
D.
result in stability theory
chosen
A result in stability theory is a formal theorem or proposition that characterizes when and how solutions of a system (often differential or dynamical) remain bounded, converge, or behave predictably under small perturbations or over time.
-
E.
discrete analogue of differential calculus
A discrete analogue of differential calculus is a mathematical framework that extends concepts like derivatives, integrals, and differential equations to functions defined on discrete domains, typically using difference operators and summation.
- 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_69e2458f7d008190901dccbaebeaba24 |
completed | April 17, 2026, 2:37 p.m. |
Created at: April 17, 2026, 3:43 p.m.