Triple
T17772203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaussian unitary ensemble |
E443666
|
entity |
| Predicate | eigenvalueDistribution |
P128209
|
FINISHED |
| Object | determinantal point process |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: determinantal point process | Statement: [Gaussian unitary ensemble, eigenvalueDistribution, determinantal point process]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eigenvalueDistribution Context triple: [Gaussian unitary ensemble, eigenvalueDistribution, determinantal point process]
-
A.
eigenvalueStatistics
Indicates that one entity characterizes or provides information about the distribution or behavior of the eigenvalues associated with another entity.
-
B.
jointEigenvalueDensity
chosen
Indicates the relationship that assigns a probability density to each possible combination of eigenvalues considered jointly, rather than individually.
-
C.
areEigenfunctionsOf
Indicates that certain functions serve as eigenfunctions corresponding to a specified operator or transformation.
-
D.
hasEquidistribution
Indicates that something is distributed uniformly or evenly across a given set, space, or range.
-
E.
spectralTheory
Indicates the relationship between an operator (or matrix) and the structure of its spectrum—its eigenvalues, eigenvectors, and related spectral properties—typically within a functional-analytic or linear-algebraic context.
- F. None of above.
Provenance (3 batches)
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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e486005770819085d637279b2334eb |
completed | April 19, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:11 a.m.