Triple

T10803634
Position Surface form Disambiguated ID Type / Status
Subject Ornstein–Uhlenbeck process E254905 entity
Predicate hasDiffusionTerm P38108 FINISHED
Object σ 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: σ | Statement: [Ornstein–Uhlenbeck process, hasDiffusionTerm, σ]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDiffusionTerm
Context triple: [Ornstein–Uhlenbeck process, hasDiffusionTerm, σ]
  • A. hasDerivativeTerm
    Indicates that one term is derived or obtained from another term, typically through a transformation, calculation, or logical inference.
  • B. isDifferential
    Indicates that one quantity represents the infinitesimal change or derivative of another with respect to a given variable.
  • C. hasDerivative
    Indicates that one entity is derived, obtained, or produced from another through some transformation, process, or modification.
  • D. hasNoiseTerm chosen
    Indicates that a given expression, model, or equation includes an additional noise term representing random or unexplained variation.
  • E. hasKineticTerm
    Indicates that an entity possesses a kinetic energy or motion-related term in its mathematical or physical description.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7336feff88190b638b7d62d34da0e completed April 9, 2026, 5:04 a.m.
PD Predicate disambiguation batch_69d6f3188f00819094ee8d65b187a333 completed April 9, 2026, 12:30 a.m.
Created at: April 8, 2026, 9:18 p.m.