Triple

T18462461
Position Surface form Disambiguated ID Type / Status
Subject Laurent El Ghaoui E451071 entity
Predicate hasPublication P80 FINISHED
Object Robust Quadratic Programming — 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: Robust Quadratic Programming | Statement: [Laurent El Ghaoui, hasPublication, Robust Quadratic Programming]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Robust Quadratic Programming
Context triple: [Laurent El Ghaoui, hasPublication, Robust Quadratic Programming]
  • A. Convex Optimization
    Convex Optimization is a widely used graduate-level textbook that systematically develops the theory, algorithms, and applications of convex optimization problems in engineering, statistics, and applied mathematics.
  • B. SQP
    SQP is the ICAO airline designator assigned to SkyUp Airlines, a Ukrainian low-cost carrier.
  • C. Constrained Control and Estimation
    "Constrained Control and Estimation" is a technical book that develops theory and methods for designing control and estimation systems subject to practical constraints, widely used in advanced control engineering and research.
  • D. Nonlinear programming
    Nonlinear programming is a branch of mathematical optimization focused on finding optimal solutions to problems where the objective function or constraints are nonlinear.
  • E. Linear Matrix Inequalities in System and Control Theory
    "Linear Matrix Inequalities in System and Control Theory" is a foundational monograph that systematically develops the theory and applications of linear matrix inequalities for analysis and design in modern control engineering.
  • 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: Robust Quadratic Programming
Target entity description: Robust Quadratic Programming is an optimization framework that extends classical quadratic programming to handle uncertainty in data and constraints, ensuring solutions remain feasible and near-optimal under worst-case variations.
  • A. Convex Optimization
    Convex Optimization is a widely used graduate-level textbook that systematically develops the theory, algorithms, and applications of convex optimization problems in engineering, statistics, and applied mathematics.
  • B. SQP
    SQP is the ICAO airline designator assigned to SkyUp Airlines, a Ukrainian low-cost carrier.
  • C. Constrained Control and Estimation
    "Constrained Control and Estimation" is a technical book that develops theory and methods for designing control and estimation systems subject to practical constraints, widely used in advanced control engineering and research.
  • D. Nonlinear programming
    Nonlinear programming is a branch of mathematical optimization focused on finding optimal solutions to problems where the objective function or constraints are nonlinear.
  • E. Linear Matrix Inequalities in System and Control Theory
    "Linear Matrix Inequalities in System and Control Theory" is a foundational monograph that systematically develops the theory and applications of linear matrix inequalities for analysis and design in modern control engineering.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e52a80a2bc81909ec14811577a311d completed April 19, 2026, 7:18 p.m.
Created at: April 10, 2026, 11:33 a.m.