SOR
E621090
SOR is an iterative numerical method used to accelerate the convergence of solving large systems of linear equations, particularly in scientific and engineering computations.
All labels observed (1)
| Label | Occurrences |
|---|---|
| SOR canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6833218 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: SOR Context triple: [Successive Over-Relaxation, hasAbbreviation, SOR]
-
A.
SER
SER is the commonly used abbreviation for South Eastern Railway, a major railway zone in India.
-
B.
SR
SR is the postcode area in North East England that covers Sunderland and surrounding parts of Tyne and Wear and County Durham.
-
C.
SR
SR is the two-letter ISO 3166-1 alpha-2 country code assigned to Suriname.
-
D.
ORS
ORS is the commonly used abbreviation for the Oregon Revised Statutes, the codified laws governing the U.S. state of Oregon.
-
E.
SO
SO is the New York Stock Exchange ticker symbol for Southern Company, a major U.S. electric and gas utility holding company based in the Southeast.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: SOR Target entity description: SOR is an iterative numerical method used to accelerate the convergence of solving large systems of linear equations, particularly in scientific and engineering computations.
-
A.
SER
SER is the commonly used abbreviation for South Eastern Railway, a major railway zone in India.
-
B.
SR
SR is the postcode area in North East England that covers Sunderland and surrounding parts of Tyne and Wear and County Durham.
-
C.
SR
SR is the two-letter ISO 3166-1 alpha-2 country code assigned to Suriname.
-
D.
ORS
ORS is the commonly used abbreviation for the Oregon Revised Statutes, the codified laws governing the U.S. state of Oregon.
-
E.
SO
SO is the New York Stock Exchange ticker symbol for Southern Company, a major U.S. electric and gas utility holding company based in the Southeast.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
iterative numerical method
ⓘ
linear system solver ⓘ |
| advantage | simple to implement ⓘ |
| alsoCalled | over-relaxation method ⓘ |
| analyzedUsing | spectral radius of iteration matrix ⓘ |
| appliedTo |
Poisson equation
NERFINISHED
ⓘ
discretized partial differential equations ⓘ elliptic PDEs ⓘ sparse linear systems ⓘ |
| assumes | linear system Ax = b ⓘ |
| basedOn | Gauss–Seidel method NERFINISHED ⓘ |
| belongsTo | numerical linear algebra ⓘ |
| canBe |
over-relaxation when relaxation factor is greater than 1
ⓘ
under-relaxation when relaxation factor is less than 1 ⓘ |
| canBeCombinedWith | multigrid methods ⓘ |
| category | stationary iterative method ⓘ |
| convergenceDependsOn |
choice of relaxation factor
ⓘ
spectral radius of iteration matrix ⓘ |
| convergesIf | spectral radius of iteration matrix is less than 1 ⓘ |
| fullName | Successive Over-Relaxation NERFINISHED ⓘ |
| generalizationOf | Gauss–Seidel method (when relaxation factor equals 1) NERFINISHED ⓘ |
| goal | reduce number of iterations to reach a given accuracy ⓘ |
| hasParameter | relaxation factor ⓘ |
| improves | rate of convergence compared to Gauss–Seidel ⓘ |
| iterationMatrixDependsOn | matrix splitting A = D - L - U ⓘ |
| limitation | may converge slowly for poorly conditioned systems ⓘ |
| modifies | Gauss–Seidel iteration with relaxation factor ⓘ |
| oftenUsedIn |
computational fluid dynamics
ⓘ
computational physics ⓘ finite difference methods ⓘ finite element methods ⓘ |
| oftenUsedWith | grid-based discretizations ⓘ |
| performanceAffectedBy |
matrix conditioning
ⓘ
problem size ⓘ |
| relatedTo |
Conjugate Gradient method
NERFINISHED
ⓘ
Gauss–Seidel method NERFINISHED ⓘ Jacobi method NERFINISHED ⓘ |
| requires |
iterative update of solution vector
ⓘ
splitting of coefficient matrix ⓘ |
| specialCaseOf | relaxation methods ⓘ |
| tunedBy | experimentally chosen relaxation factor ⓘ |
| typicalRelaxationFactorRange | between 1 and 2 for over-relaxation ⓘ |
| typicalUseCase | large, sparse, structured linear systems ⓘ |
| usedFor |
accelerating convergence of iterative methods
ⓘ
solving large systems of linear equations ⓘ |
| usedIn |
engineering computations
ⓘ
scientific computations ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Subject: SOR Description of subject: SOR is an iterative numerical method used to accelerate the convergence of solving large systems of linear equations, particularly in scientific and engineering computations.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.