Triple

T25602646
Position Surface form Disambiguated ID Type / Status
Subject Cover’s theorem on the separability of patterns E641827 entity
Predicate instanceOf P0 FINISHED
Object result in statistical learning theory C8028 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: result in statistical learning theory
Context triple: [Cover’s theorem on the separability of patterns, instanceOf, result in statistical learning theory]
  • A. learning theory
    Learning theory is the conceptual framework that explains how knowledge and skills are acquired, processed, retained, and applied through experience, instruction, and practice.
  • B. statistical classification
    Statistical classification is the process of assigning items or observations to predefined categories or classes based on their measured features using probabilistic or algorithmic decision rules.
  • C. result in probability theory chosen
    In probability theory, a result is a formally stated and proven fact—such as a theorem, lemma, or corollary—that describes a property or relationship involving probabilistic concepts like random variables, events, or distributions.
  • D. machine learning book
    A machine learning book is a structured, written resource that explains the theories, algorithms, and practical applications of machine learning to help readers understand and apply data-driven modeling techniques.
  • E. machine learning paradigm
    A machine learning paradigm is a conceptual framework that defines how models learn from data, including the assumptions, learning objectives, and training procedures that guide the development and application of algorithms.
  • 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_69e75dc6ccf081908d49578fd36a76d5 completed April 21, 2026, 11:21 a.m.
Created at: April 21, 2026, 4:36 p.m.