Triple

T2325304
Position Surface form Disambiguated ID Type / Status
Subject Ornstein–Uhlenbeck process E48273 entity
Predicate hasMeanFunction P3634 FINISHED
Object exponential reversion to long-term mean 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: exponential reversion to long-term mean | Statement: [Ornstein–Uhlenbeck process, hasMeanFunction, exponential reversion to long-term mean]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMeanFunction
Context triple: [Ornstein–Uhlenbeck process, hasMeanFunction, exponential reversion to long-term mean]
  • A. hasMean chosen
    Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
  • B. hasStatisticalFunctions
    Indicates that one entity provides or supports statistical operations or capabilities for another entity.
  • C. hasDistributionFunction
    Indicates that an entity is associated with a specific distribution function that characterizes how its values or occurrences are probabilistically or statistically distributed.
  • D. hadFunction
    Indicates that an entity previously served or fulfilled a particular role, purpose, or function.
  • E. hasMomentGeneratingFunction
    Indicates that a random variable or probability distribution possesses a well-defined moment generating function characterizing all of its moments.
  • 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_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.
Created at: March 4, 2026, 7:50 p.m.