Triple
T36564801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atangana–Baleanu–Caputo derivative |
E901944
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | generalized derivative operator |
C28455
|
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: generalized derivative operator Context triple: [Atangana–Baleanu–Caputo derivative, instanceOf, generalized derivative operator]
-
A.
linear differential operator
A linear differential operator is a mapping that takes a function as input and returns a new function formed by a linear combination of the function and its derivatives.
-
B.
fractional derivative
chosen
A fractional derivative is a generalization of the ordinary derivative to non-integer (fractional) orders, capturing intermediate rates of change and memory effects in functions and systems.
-
C.
geometric operator
A geometric operator is a mathematical construct that acts on geometric objects (such as points, vectors, or shapes) to transform, relate, or measure them while respecting the underlying geometric structure.
-
D.
elliptic differential operator
An elliptic differential operator is a linear differential operator whose principal symbol is invertible away from the zero section, ensuring strong regularity and smoothing properties for its solutions.
-
E.
non-local operator
A non-local operator is a mathematical operator whose action at a point depends on the values of a function over an extended region or the entire domain, rather than solely on local information at that point.
- 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_69f76e6416708190a9754b8c52d4e453 |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:11 p.m.