Triple

T14012481
Position Surface form Disambiguated ID Type / Status
Subject Yakov Sinai E337117 entity
Predicate notableWork P4 FINISHED
Object Kolmogorov–Sinai entropy E695939 NE 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: Kolmogorov–Sinai entropy | Statement: [Yakov Sinai, notableWork, Kolmogorov–Sinai entropy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kolmogorov–Sinai entropy
Context triple: [Yakov Sinai, notableWork, Kolmogorov–Sinai entropy]
  • A. Kolmogorov–Sinai entropy chosen
    Kolmogorov–Sinai entropy is a fundamental invariant in dynamical systems theory that quantifies the average rate of information production or unpredictability of a measure-preserving transformation.
  • B. Rényi entropy
    Rényi entropy is a generalized measure of information and uncertainty that extends Shannon entropy by introducing a tunable order parameter to emphasize different aspects of a probability distribution.
  • C. Lyapunov exponents
    Lyapunov exponents are quantitative measures in dynamical systems theory that characterize the rates at which nearby trajectories diverge or converge, indicating the presence and strength of chaos.
  • D. Shannon entropy
    Shannon entropy is a fundamental measure in information theory that quantifies the average uncertainty or information content in a random variable or message source.
  • E. Khinchin–Kolmogorov theorem
    The Khinchin–Kolmogorov theorem is a fundamental result in probability theory that provides conditions under which series of independent random variables converge almost surely.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2f37d11481909159bdb9e1e8d38e completed April 14, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbacaa16e88190995fd86951fb54e6 completed May 6, 2026, 9:03 p.m.
Created at: April 9, 2026, 10:19 p.m.