Triple
T7871793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacobi polynomials |
E182753
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | special functions |
C11532
|
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: special functions Context triple: [Jacobi polynomials, instanceOf, special functions]
-
A.
special function
chosen
A special function is a mathematically well-studied function, often arising as a solution to differential equations or integrals, that has established names, properties, and applications across many areas of science and engineering.
-
B.
method for asymptotic evaluation of integrals
A method for asymptotic evaluation of integrals is a collection of analytical techniques used to approximate the behavior of integrals in limiting regimes (such as large parameters) by extracting their dominant contributions.
-
C.
Dirichlet series
A Dirichlet series is an infinite series of the form ∑ₙ₌₁^∞ aₙ n^(-s), where s is a complex variable and aₙ are complex coefficients, used extensively in analytic number theory to study arithmetic functions and L-functions.
-
D.
L-function
An L-function is a complex analytic function, typically expressed as a Dirichlet series with an Euler product, that encodes deep arithmetic information about objects such as numbers, fields, or algebraic varieties.
-
E.
result in mathematical physics
A result in mathematical physics is a rigorously proven statement that connects precise mathematical structures with physical theories, often clarifying, justifying, or predicting phenomena within a formal framework.
- 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_69ca82894d9081908a832bfce71a4714 |
completed | March 30, 2026, 2:02 p.m. |
Created at: March 30, 2026, 4:56 p.m.