Triple

T27176407
Position Surface form Disambiguated ID Type / Status
Subject Lyapunov condition E683054 entity
Predicate instanceOf P0 FINISHED
Object condition for central limit theorem C26950 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: condition for central limit theorem
Context triple: [Lyapunov condition, instanceOf, condition for central limit theorem]
  • A. 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.
  • B. quantitative central limit theorem
    The quantitative central limit theorem provides explicit bounds on how quickly the distribution of normalized sums of random variables converges to the normal distribution, typically in terms of metrics like the Kolmogorov or Wasserstein distance.
  • C. criterion for uniform convergence
    A criterion for uniform convergence is a condition or set of conditions that allows one to determine whether a sequence (or series) of functions converges uniformly to a limiting function on a given domain.
  • D. criterion for convergence chosen
    A criterion for convergence is a specific test or condition used to determine whether a given sequence or series approaches a finite limit as its index or number of terms increases.
  • E. empirical rule
    The empirical rule is a statistical guideline stating that for a normal distribution, approximately 68% of data fall within one standard deviation of the mean, 95% within two, and 99.7% within three.
  • 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_69eefad086808190ab89816c0c300476 completed April 27, 2026, 5:57 a.m.
Created at: April 27, 2026, 9:26 a.m.