Triple

T23507773
Position Surface form Disambiguated ID Type / Status
Subject Leonid Levin E572330 entity
Predicate notableIdea P4 FINISHED
Object universal search algorithm (Levin search) NE NERFINISHED

How this triple was built (3 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: universal search algorithm (Levin search) | Statement: [Leonid Levin, notableIdea, universal search algorithm (Levin search)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: universal search algorithm (Levin search)
Context triple: [Leonid Levin, notableIdea, universal search algorithm (Levin search)]
  • A. Generalized Search Tree
    Generalized Search Tree is a flexible, balanced tree data structure framework that supports building custom index types for complex data and queries, often used in database systems.
  • B. Boyer–Moore string-search algorithm
    The Boyer–Moore string-search algorithm is a highly efficient pattern-matching algorithm that scans text from right to left and uses precomputed shift rules to skip sections of the text, making it one of the fastest practical algorithms for substring search.
  • C. Thompson's algorithm
    Thompson's algorithm is a classic computer science method for converting regular expressions into nondeterministic finite automata (NFAs), widely used in pattern matching and lexical analysis.
  • D. Davis–Putnam algorithm
    The Davis–Putnam algorithm is a pioneering procedure in automated theorem proving and propositional logic satisfiability that laid foundational groundwork for modern SAT solvers.
  • E. Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability
    Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability is a foundational monograph by Marcus Hutter that rigorously develops a formal, mathematical theory of general artificial intelligence based on algorithmic information theory and optimal sequential decision-making.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: universal search algorithm (Levin search)
Target entity description: The universal search algorithm, or Levin search, is a theoretically optimal method for solving search and optimization problems by systematically exploring all possible algorithms in parallel, weighted by their description length and runtime.
  • A. Generalized Search Tree
    Generalized Search Tree is a flexible, balanced tree data structure framework that supports building custom index types for complex data and queries, often used in database systems.
  • B. Boyer–Moore string-search algorithm
    The Boyer–Moore string-search algorithm is a highly efficient pattern-matching algorithm that scans text from right to left and uses precomputed shift rules to skip sections of the text, making it one of the fastest practical algorithms for substring search.
  • C. Thompson's algorithm
    Thompson's algorithm is a classic computer science method for converting regular expressions into nondeterministic finite automata (NFAs), widely used in pattern matching and lexical analysis.
  • D. Davis–Putnam algorithm
    The Davis–Putnam algorithm is a pioneering procedure in automated theorem proving and propositional logic satisfiability that laid foundational groundwork for modern SAT solvers.
  • E. Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability
    Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability is a foundational monograph by Marcus Hutter that rigorously develops a formal, mathematical theory of general artificial intelligence based on algorithmic information theory and optimal sequential decision-making.
  • F. None of above. chosen

Provenance (2 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_69e245b5e4208190bac8a6509867e394 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a901c9908190a781e79fe8b96743 completed April 29, 2026, 6:45 a.m.
Created at: April 17, 2026, 6:07 p.m.