Triple

T7906511
Position Surface form Disambiguated ID Type / Status
Subject Kolmogorov complexity E183589 entity
Predicate hasVariant P455 FINISHED
Object prefix-free Kolmogorov complexity E183589 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: prefix-free Kolmogorov complexity | Statement: [Kolmogorov complexity, hasVariant, prefix-free Kolmogorov complexity]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: prefix-free Kolmogorov complexity
Context triple: [Kolmogorov complexity, hasVariant, prefix-free Kolmogorov complexity]
  • A. Kolmogorov complexity chosen
    Kolmogorov complexity is a measure of the amount of information in an object, defined as the length of the shortest computer program that can produce it.
  • B. Blum complexity measures
    Blum complexity measures are a formal framework in computational complexity theory that rigorously define and compare the resource usage (such as time or space) of algorithms via axiomatic conditions.
  • C. Martin-Löf randomness
    Martin-Löf randomness is a rigorous mathematical notion of randomness for infinite binary sequences, defined via effectively null sets and closely connected to algorithmic information theory.
  • D. Kolmogorov–Sinai entropy
    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.
  • E. Turing degrees
    Turing degrees are an abstract classification of sets of natural numbers or decision problems according to their relative level of algorithmic unsolvability or computational complexity under Turing reducibility.
  • 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_69ca828dec0c81908b8f55a4dbbb53ff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a5871b8819087ad69c116c40091 completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbdfe21f9081909d45565867ac7436 completed March 31, 2026, 2:53 p.m.
Created at: March 30, 2026, 5:03 p.m.