Triple
T18462464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurent El Ghaoui |
E451071
|
entity |
| Predicate | hasPublication |
P80
|
FINISHED |
| Object | Robust Optimization: Theory and Applications |
—
|
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 Optimization: Theory and Applications | Statement: [Laurent El Ghaoui, hasPublication, Robust Optimization: Theory and Applications]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robust Optimization: Theory and Applications Context triple: [Laurent El Ghaoui, hasPublication, Robust Optimization: Theory and Applications]
-
A.
Combinatorial Optimization: Algorithms and Complexity
Combinatorial Optimization: Algorithms and Complexity is a foundational textbook that systematically develops the theory and algorithms of combinatorial optimization, emphasizing computational complexity and algorithmic efficiency.
-
B.
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.
-
C.
Gomory cuts in integer programming
Gomory cuts in integer programming are a class of cutting-plane techniques that iteratively refine linear programming relaxations to find optimal integer solutions to mixed-integer optimization problems.
-
D.
Optimization over Time
"Optimization over Time" is a seminal work by Peter Whittle that develops mathematical methods for making optimal sequential decisions in dynamic and stochastic systems.
-
E.
Risk-Sensitive Optimal Control
Risk-Sensitive Optimal Control is a foundational work in control theory that develops methods for designing controllers that explicitly account for uncertainty and variability in system performance.
- 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 Optimization: Theory and Applications Target entity description: "Robust Optimization: Theory and Applications" is a scholarly work that develops the mathematical foundations of robust optimization and demonstrates their use in designing decision-making models that remain effective under uncertainty.
-
A.
Combinatorial Optimization: Algorithms and Complexity
Combinatorial Optimization: Algorithms and Complexity is a foundational textbook that systematically develops the theory and algorithms of combinatorial optimization, emphasizing computational complexity and algorithmic efficiency.
-
B.
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.
-
C.
Gomory cuts in integer programming
Gomory cuts in integer programming are a class of cutting-plane techniques that iteratively refine linear programming relaxations to find optimal integer solutions to mixed-integer optimization problems.
-
D.
Optimization over Time
"Optimization over Time" is a seminal work by Peter Whittle that develops mathematical methods for making optimal sequential decisions in dynamic and stochastic systems.
-
E.
Risk-Sensitive Optimal Control
Risk-Sensitive Optimal Control is a foundational work in control theory that develops methods for designing controllers that explicitly account for uncertainty and variability in system performance.
- 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.