Triple
T35332719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kantorovich problem in optimal transport |
E1020368
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | linear programming problem |
C11579
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: linear programming problem Context triple: [Kantorovich problem in optimal transport, instanceOf, linear programming problem]
-
A.
mathematical program
chosen
A mathematical program is an optimization model that seeks to minimize or maximize an objective function subject to a set of mathematical constraints.
-
B.
combinatorial optimization problem
A combinatorial optimization problem is a mathematical task of finding an optimal object (such as a subset, sequence, or arrangement) from a finite but typically large set of discrete possibilities, subject to given constraints.
-
C.
integer programming technique
An integer programming technique is an optimization method that finds the best solution to a mathematical model where some or all decision variables are restricted to integer values, often used for discrete decision-making problems.
-
D.
mathematical optimization modeling language
A mathematical optimization modeling language is a high-level, declarative language used to express optimization problems (variables, objectives, and constraints) in a form that can be automatically translated and solved by optimization solvers.
-
E.
mathematical problem
A mathematical problem is a question or task that requires the application of mathematical concepts, methods, or reasoning to find a solution or demonstrate a result.
- F. None of above.
Provenance (1 batch)
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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4:03 p.m.