Triple

T17752873
Position Surface form Disambiguated ID Type / Status
Subject Dyson index β E443154 entity
Predicate value2AssociatedWith P33135 FINISHED
Object Gaussian unitary ensemble NE NERFINISHED

How this triple was built (3 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: Gaussian unitary ensemble | Statement: [Dyson index β, value2AssociatedWith, Gaussian unitary ensemble]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaussian unitary ensemble
Context triple: [Dyson index β, value2AssociatedWith, Gaussian unitary ensemble]
  • A. Gaussian unitary ensemble chosen
    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.
  • B. Gaussian orthogonal ensemble
    The Gaussian orthogonal ensemble is a fundamental random matrix ensemble of real symmetric matrices with Gaussian-distributed entries, central to the study of eigenvalue statistics and universality in random matrix theory.
  • C. 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.
  • D. Gaussian ensembles
    Gaussian ensembles are families of random matrices characterized by specific symmetry properties that determine the statistical distribution of their eigenvalues.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: value2AssociatedWith
Context triple: [Dyson index β, value2AssociatedWith, Gaussian unitary ensemble]
  • A. associatedValue chosen
    Indicates that one entity is linked to another entity that serves as its corresponding or contextually related value.
  • B. valueRelation
    Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
  • C. value
    Indicates that one entity possesses, represents, or corresponds to a particular quantity, quality, or assigned worth.
  • D. valueDefinedBy
    Indicates that the value of one entity is determined, specified, or constrained by another entity.
  • E. valuedBy
    Indicates that one entity is regarded as important, useful, or held in high esteem by another entity.
  • 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_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.
Created at: April 10, 2026, 10:10 a.m.