Triple

T20836565
Position Surface form Disambiguated ID Type / Status
Subject SAT problem E512973 entity
Predicate canonicalReference P5454 FINISHED
Object Cook–Levin theorem NE NERFINISHED

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: Cook–Levin theorem | Statement: [SAT problem, canonicalReference, Cook–Levin theorem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cook–Levin theorem
Context triple: [SAT problem, canonicalReference, Cook–Levin theorem]
  • A. Cook–Levin theorem chosen
    The Cook–Levin theorem is a foundational result in computational complexity theory that established the Boolean satisfiability problem (SAT) as the first NP-complete problem, launching the theory of NP-completeness.
  • B. Papadimitriou–Yannakakis theorem
    The Papadimitriou–Yannakakis theorem is a fundamental result in computational complexity theory that characterizes the complexity of certain optimization and approximation problems, particularly in relation to classes like NP and the theory of approximation algorithms.
  • C. Valiant–Vazirani theorem
    The Valiant–Vazirani theorem is a fundamental result in computational complexity theory showing that solving unique solutions of NP problems is, under randomized reductions, as hard as solving general NP problems, with major implications for the study of randomness and hardness of approximation.
  • D. PCP theorem
    The PCP theorem is a fundamental result in computational complexity theory stating that every problem in NP has probabilistically checkable proofs that can be verified by examining only a constant number of bits, with major implications for the hardness of approximation.
  • E. P versus NP problem
    The P versus NP problem is a central unsolved question in theoretical computer science that asks whether every problem whose solution can be quickly verified by a computer can also be quickly solved by a computer.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c326daec8190bd4caa41a4b38833 completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:42 p.m.