Triple
T24313789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gale’s theorem on flows with convex costs |
E612747
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | result in mathematical optimization |
C15240
|
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: result in mathematical optimization Context triple: [Gale’s theorem on flows with convex costs, instanceOf, result in mathematical optimization]
-
A.
mathematical program
A mathematical program is an optimization model that seeks to minimize or maximize an objective function subject to a set of mathematical constraints.
-
B.
result in convex analysis
chosen
In convex analysis, a result is a formally stated and proven fact—such as a theorem, lemma, or proposition—that characterizes properties or relationships of convex sets, convex functions, or related optimization structures.
-
C.
optimization paradigm
An optimization paradigm is a conceptual framework that defines how to formulate, search for, and evaluate solutions to a problem in order to find the best (or sufficiently good) outcome under given constraints and objectives.
-
D.
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.
-
E.
result in mathematical physics
A result in mathematical physics is a rigorously proven statement that connects precise mathematical structures with physical theories, often clarifying, justifying, or predicting phenomena within a formal framework.
- 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_69e2d7da491c8190b6e6218af50923db |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 18, 2026, 1:45 a.m.