Triple
T17752821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaussian orthogonal ensemble |
E443153
|
entity |
| Predicate | eigenvalueStatistics |
P128208
|
FINISHED |
| Object | Wigner–Dyson statistics |
—
|
NE NERFINISHED |
How this triple was built (4 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: Wigner–Dyson statistics | Statement: [Gaussian orthogonal ensemble, eigenvalueStatistics, Wigner–Dyson statistics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wigner–Dyson statistics Context triple: [Gaussian orthogonal ensemble, eigenvalueStatistics, Wigner–Dyson statistics]
-
A.
Wigner surmise
The Wigner surmise is an approximate formula in random matrix theory that describes the statistical distribution of spacings between neighboring energy levels in complex quantum systems.
-
B.
Gaussian unitary ensemble
The Gaussian unitary ensemble is a fundamental random matrix ensemble of complex Hermitian matrices with statistically independent, Gaussian-distributed entries, central to quantum chaos and random matrix theory.
-
C.
Wigner matrices
Wigner matrices are large random symmetric (or Hermitian) matrices with independent, identically distributed entries (up to symmetry) that serve as a fundamental model in random matrix theory for studying eigenvalue statistics and universal spectral behavior.
-
D.
Gaussian symplectic ensemble
The Gaussian symplectic ensemble is a random matrix ensemble of self-dual quaternionic Hermitian matrices used in random matrix theory to model systems with time-reversal symmetry and strong spin–orbit coupling.
-
E.
Wigner semicircle law
The Wigner semicircle law is a fundamental result in random matrix theory that describes how the eigenvalues of large random symmetric (or Hermitian) matrices are distributed according to a characteristic semicircular density.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wigner–Dyson statistics Target entity description: Wigner–Dyson statistics describe the characteristic level-spacing distributions of eigenvalues in random matrix ensembles, capturing universal spectral correlations in complex quantum and chaotic systems.
-
A.
Wigner surmise
chosen
The Wigner surmise is an approximate formula in random matrix theory that describes the statistical distribution of spacings between neighboring energy levels in complex quantum systems.
-
B.
Gaussian unitary ensemble
The Gaussian unitary ensemble is a fundamental random matrix ensemble of complex Hermitian matrices with statistically independent, Gaussian-distributed entries, central to quantum chaos and random matrix theory.
-
C.
Wigner matrices
Wigner matrices are large random symmetric (or Hermitian) matrices with independent, identically distributed entries (up to symmetry) that serve as a fundamental model in random matrix theory for studying eigenvalue statistics and universal spectral behavior.
-
D.
Gaussian symplectic ensemble
The Gaussian symplectic ensemble is a random matrix ensemble of self-dual quaternionic Hermitian matrices used in random matrix theory to model systems with time-reversal symmetry and strong spin–orbit coupling.
-
E.
Wigner semicircle law
The Wigner semicircle law is a fundamental result in random matrix theory that describes how the eigenvalues of large random symmetric (or Hermitian) matrices are distributed according to a characteristic semicircular density.
- F. None of above.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eigenvalueStatistics Context triple: [Gaussian orthogonal ensemble, eigenvalueStatistics, Wigner–Dyson statistics]
-
A.
eigenvaluesCorrespondTo
Indicates that the eigenvalues are associated in a defined way with another mathematical object or set, such as arising from or matching the spectrum of that object.
-
B.
areEigenfunctionsOf
Indicates that certain functions serve as eigenfunctions corresponding to a specified operator or transformation.
-
C.
eigenvectorsCorrespondTo
Indicates that one set of eigenvectors is associated with, or corresponds in a defined way to, another set of eigenvectors (typically via a shared transformation, matrix, or mapping).
-
D.
CPEigenstate
Indicates that a quantum state is an eigenstate of the combined charge-conjugation and parity (CP) symmetry operator, remaining unchanged up to a phase under the CP transformation.
-
E.
hasCPApproximateEigenvalue
Indicates that one entity is an approximate eigenvalue of a completely positive (CP) map or operator associated with another entity.
- F. None of above. chosen
Provenance (4 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841c0540819093a32d759775c61f |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3cfab7edc8190b663282d565a0389 |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10:10 a.m.