Triple

T12597364
Position Surface form Disambiguated ID Type / Status
Subject Runge–Kutta methods E300766 entity
Predicate hasSubclass P1244 FINISHED
Object Gauss–Legendre Runge–Kutta methods E697759 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: Gauss–Legendre Runge–Kutta methods | Statement: [Runge–Kutta methods, hasSubclass, Gauss–Legendre Runge–Kutta methods]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gauss–Legendre Runge–Kutta methods
Context triple: [Runge–Kutta methods, hasSubclass, Gauss–Legendre Runge–Kutta methods]
  • A. Runge–Kutta methods
    Runge–Kutta methods are a family of iterative techniques for numerically solving ordinary differential equations with higher accuracy than simple one-step schemes.
  • B. Godunov-type schemes
    Godunov-type schemes are a class of finite-volume numerical methods for solving hyperbolic conservation laws that use Riemann solvers to accurately capture shock waves and discontinuities.
  • C. classical fourth-order Runge–Kutta method
    The classical fourth-order Runge–Kutta method is a widely used, higher-accuracy numerical technique for solving ordinary differential equations by combining multiple intermediate slope evaluations within each integration step.
  • D. Euler’s method for numerical integration
    Euler’s method for numerical integration is a simple first-order numerical procedure used to approximate solutions to ordinary differential equations by stepping forward in small increments.
  • E. Gaussian quadrature rules chosen
    Gaussian quadrature rules are numerical integration methods that approximate definite integrals by optimally choosing evaluation points and weights to achieve exactness for polynomials up to a high degree.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954cf33b88190bff339fcd3142cc8 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ec75fc08190aa13cbb0161eb35c completed May 2, 2026, 8:29 p.m.
Created at: April 9, 2026, 5:08 p.m.