Triple

T17520655
Position Surface form Disambiguated ID Type / Status
Subject Support Vector Machine E426671 entity
Predicate usesConcept P531 FINISHED
Object Lagrange multipliers — 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: Lagrange multipliers | Statement: [Support Vector Machine, usesConcept, Lagrange multipliers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lagrange multipliers
Context triple: [Support Vector Machine, usesConcept, Lagrange multipliers]
  • A. Lagrange multipliers chosen
    Lagrange multipliers are a mathematical optimization technique used to find the extrema of functions subject to equality constraints.
  • B. Karush–Kuhn–Tucker conditions
    The Karush–Kuhn–Tucker conditions are fundamental optimality criteria in nonlinear programming that generalize Lagrange multipliers to handle inequality constraints.
  • C. Euler–Lagrange equation
    The Euler–Lagrange equation is a fundamental differential equation in the calculus of variations that provides the condition for a function to make a functional stationary, forming the basis of Lagrangian mechanics and many physical theories.
  • D. KKT conditions
    KKT conditions are a set of necessary (and under certain conditions, sufficient) optimality conditions used in nonlinear programming to characterize solutions of constrained optimization problems.
  • E. Lagrangian function
    The Lagrangian function is a mathematical construct that combines an objective function with its constraints, widely used in optimization and variational calculus to analyze and solve constrained problems.
  • 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d23cf08190925510344fa36f57 completed April 19, 2026, 3:58 a.m.
Created at: April 10, 2026, 5:49 a.m.