Triple

T15502424
Position Surface form Disambiguated ID Type / Status
Subject Khinchin's law of the iterated logarithm E378993 entity
Predicate instanceOf P0 FINISHED
Object law of the iterated logarithm C1599 CONCEPT FINISHED

How this triple was built (1 step)

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.

CD Concept disambiguation gpt-5-mini-2025-08-07
Target class: law of the iterated logarithm
Context triple: [Khinchin's law of the iterated logarithm, instanceOf, law of the iterated logarithm]
  • A. tool in large deviation theory
    A tool in large deviation theory is a mathematical method or result—such as rate functions, the Gartner–Ellis theorem, or contraction principles—used to quantify and analyze the exponentially small probabilities of rare events in stochastic systems.
  • B. stochastic process chosen
    A stochastic process is a collection of random variables indexed by time or space that describes the evolution of a system subject to inherent randomness.
  • C. random variable functional
    A random variable functional is a mapping that takes one or more random variables (or their distributions) as input and returns a real-valued quantity summarizing some aspect of their probabilistic behavior.
  • D. object in optimal stopping theory
    An object in optimal stopping theory is an abstract entity (such as a stochastic process, payoff function, or stopping rule) whose evolution or evaluation over time determines when it is best to stop observing and take an action to maximize expected reward or minimize expected cost.
  • E. central limit theorem
    The central limit theorem states that, under broad conditions, the sum (or average) of a large number of independent, identically distributed random variables tends to follow a normal distribution, regardless of the original variables’ distribution.
  • F. None of above.

Provenance (1 batch)

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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
Created at: April 10, 2026, 3:54 a.m.