Triple
T33761220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dyson integral |
E865109
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | object in random matrix theory |
C39118
|
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: object in random matrix theory Context triple: [Dyson integral, instanceOf, object in random matrix theory]
-
A.
random matrix ensemble
chosen
A random matrix ensemble is a collection of matrices whose entries are random variables specified by a probability distribution, studied to understand the statistical properties of their eigenvalues and eigenvectors.
-
B.
parameter in random matrix theory
A parameter in random matrix theory is a variable (such as matrix size, symmetry class index, or coupling constant) that controls the statistical properties and limiting behavior of ensembles of random matrices.
-
C.
result in probabilistic number theory
A result in probabilistic number theory is a theorem or statement that describes the typical or average behavior of arithmetic objects (such as integers, primes, or multiplicative functions) using probabilistic models and methods.
-
D.
object in invariant theory
An object in invariant theory is a mathematical entity, such as a vector space, polynomial ring, or group action, whose structure and symmetries are studied through the functions or quantities that remain unchanged under a specified group of transformations.
-
E.
Green’s function in Euclidean space
A Green’s function in Euclidean space is a fundamental solution to a linear differential operator that represents the response at one point due to a unit source located at another point, enabling the construction of solutions to boundary value problems via superposition.
- 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_69f3498d3b748190aa3c4006c1f32f38 |
completed | April 30, 2026, 12:22 p.m. |
Created at: May 1, 2026, 1:45 a.m.