typeOfOptimality
P27210
predicate
Indicates that one entity specifies the particular notion or criterion of optimality that characterizes another entity’s optimal status or solution.
All labels observed (6)
| Label | Occurrences |
|---|---|
| optimizationCriterion | 17 |
| optimizationProperty | 2 |
| isOptimalIn | 1 |
| maximizationYields | 1 |
| typeOfOptimality canonical | 1 |
| usesOptimizationCriterion | 1 |
Description generation (PDg)
The one-sentence description above was generated by prompting gpt-5.1 with the predicate name and this instruction.
Instruction
Given a predicate that represents a relationship or action between entities, generate a one-sentence description explaining its meaning. # Instructions Focus on describing the relationship, not the entities themselves. # Response Format Begin the description with \' Indicates...\'
Input
Predicate: typeOfOptimality
Generated description
Indicates that one entity specifies the particular notion or criterion of optimality that characterizes another entity’s optimal status or solution.
Sample triples (23)
| Subject | Object |
|---|---|
| Gauss–Markov theorem | minimum variance ⓘ |
|
Boltzmann–Gibbs entropy in statistical mechanics
surface form:
Boltzmann–Gibbs entropy
|
Boltzmann distribution via predicate surface "maximizationYields" ⓘ |
| Fermat point | minimizes sum of distances to the three vertices of the triangle via predicate surface "optimizationProperty" ⓘ |
| Fermat point | gives minimal network length connecting the three vertices with one Steiner point via predicate surface "optimizationProperty" ⓘ |
| Compact Linear Collider | high luminosity at multi-TeV energies via predicate surface "optimizationCriterion" ⓘ |
|
“A New Approach to Linear Filtering and Prediction Problems”
surface form:
A New Approach to Linear Filtering and Prediction Problems
|
minimum mean-square error estimation via predicate surface "optimizationCriterion" ⓘ |
| Daubechies wavelets | maximal number of vanishing moments for a given support width via predicate surface "optimizationCriterion" ⓘ |
| Cascade-Correlation learning architecture | maximization of correlation between unit output and network residual error via predicate surface "usesOptimizationCriterion" ⓘ |
|
NR reduced capability (NR RedCap)
surface form:
NR reduced capability
|
cost efficiency via predicate surface "optimizationCriterion" ⓘ |
|
NR reduced capability (NR RedCap)
surface form:
NR reduced capability
|
energy efficiency via predicate surface "optimizationCriterion" ⓘ |
|
NR reduced capability (NR RedCap)
surface form:
NR reduced capability
|
implementation simplicity via predicate surface "optimizationCriterion" ⓘ |
| Max-3-SAT | maximize satisfied clauses rather than satisfy all via predicate surface "optimizationCriterion" ⓘ |
| Max-E3-LIN-2 | number of satisfied constraints via predicate surface "optimizationCriterion" ⓘ |
| DAXplus Minimum Variance | minimum portfolio variance via predicate surface "optimizationCriterion" ⓘ |
| Successive Under-Relaxation | trade-off between stability and speed of convergence via predicate surface "optimizationCriterion" ⓘ |
|
Roth theorem
surface form:
Roth's theorem
|
exponent of q in the approximation inequality via predicate surface "isOptimalIn" ⓘ |
| Intze principle | minimum concrete volume for required capacity via predicate surface "optimizationCriterion" ⓘ |
| Intze principle | reduction of reinforcement steel quantity via predicate surface "optimizationCriterion" ⓘ |
| MPEG-4 CELP | minimization of perceptual error via predicate surface "optimizationCriterion" ⓘ |
| Grain v1 | minimal hardware resources via predicate surface "optimizationCriterion" ⓘ |
| Grain v1 | implementation efficiency via predicate surface "optimizationCriterion" ⓘ |
| Baum–Welch algorithm | likelihood of observed data via predicate surface "optimizationCriterion" ⓘ |
| Generalized method of moments | quadratic form in sample moment conditions via predicate surface "optimizationCriterion" ⓘ |