Triple

T2325287
Position Surface form Disambiguated ID Type / Status
Subject Ornstein–Uhlenbeck process E48273 entity
Predicate hasNoiseTerm P38108 FINISHED
Object additive Brownian motion 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: additive Brownian motion | Statement: [Ornstein–Uhlenbeck process, hasNoiseTerm, additive Brownian motion]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNoiseTerm
Context triple: [Ornstein–Uhlenbeck process, hasNoiseTerm, additive Brownian motion]
  • A. noiseLevel
    Indicates the intensity or amount of sound present in a given environment or from a specific source.
  • B. hasSound
    Indicates that an entity produces, emits, or is associated with a particular sound.
  • C. usesCrosstalkCancellation
    Indicates that one entity applies crosstalk cancellation techniques to reduce or eliminate interference between signals associated with another entity.
  • D. hasVariance
    Indicates that there is a measurable degree of variability or dispersion in the values or outcomes associated with the related entities.
  • E. hasEntropy
    Indicates that an entity possesses or is characterized by a certain amount or state of entropy, typically reflecting its degree of disorder or uncertainty.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc685f05481909c863b29d1f6bacd completed March 7, 2026, 6:32 a.m.
PD Predicate disambiguation batch_69abc5909cc48190aab257313542dc49 completed March 7, 2026, 6:28 a.m.
PDg Predicate description generation batch_69abc682d094819081a96ffb77c4c42a completed March 7, 2026, 6:32 a.m.
Created at: March 4, 2026, 7:50 p.m.