Triple
T21763304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max-E3-LIN-2 |
E537215
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | constraint satisfaction optimization problem |
C44866
|
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: constraint satisfaction optimization problem Context triple: [Max-E3-LIN-2, instanceOf, constraint satisfaction optimization problem]
-
A.
combinatorial optimization problem
chosen
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.
-
B.
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.
-
C.
geometric optimization problem
A geometric optimization problem is a mathematical task that involves finding the best (e.g., shortest, largest, or most efficient) geometric configuration or measurement under given constraints.
-
D.
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.
-
E.
optimality conditions
Optimality conditions are mathematical criteria that must be satisfied by a candidate solution to ensure it is a local or global optimum of an optimization problem.
- 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
Created at: April 16, 2026, 6:51 p.m.