Triple
T16150928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirac operator |
E391906
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | first-order differential operator |
C23060
|
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: first-order differential operator Context triple: [Dirac operator, instanceOf, first-order differential operator]
-
A.
linear differential operator
chosen
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.
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.
-
C.
ordinary differential equation
An ordinary differential equation is an equation involving an unknown function of a single independent variable and its derivatives, relating them through specified functional relationships.
-
D.
linear differential equation
A linear differential equation is an equation involving an unknown function and its derivatives in which the function and its derivatives appear only to the first power and are not multiplied together, with coefficients that may depend on the independent variable.
-
E.
first integral
A first integral is a function of the variables and their derivatives that remains constant along the solutions of a differential equation, representing a conserved quantity of the system.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
Created at: April 10, 2026, 5:01 a.m.