AMPL modeling language
E645517
AMPL modeling language is a high-level algebraic language used to describe and solve large-scale mathematical optimization problems.
All labels observed (3)
| Label | Occurrences |
|---|---|
| A Mathematical Programming Language | 2 |
| AMPL modeling language canonical | 2 |
| AMPL: A Modeling Language for Mathematical Programming | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7164923 — 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.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AMPL modeling language Context triple: [Brian Kernighan, knownFor, AMPL modeling language]
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A.
SCIP
SCIP is the ICAO airport code for Mataveri International Airport, the main air gateway to Easter Island in Chile.
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B.
CVX
CVX is the stock ticker symbol for Chevron Corporation, a major American multinational energy and oil company.
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C.
BrainScript modeling language
BrainScript modeling language is a domain-specific scripting language used to define and train neural network models within the Microsoft Cognitive Toolkit (CNTK).
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D.
ADMM
ADMM is a regional forum that brings together the defence ministers of ASEAN member states to discuss and coordinate security and defence cooperation in Southeast Asia.
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E.
Simulink
Simulink is a graphical modeling and simulation environment for designing, simulating, and analyzing dynamic systems, commonly used within MATLAB for control, signal processing, and embedded system development.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AMPL modeling language Target entity description: AMPL modeling language is a high-level algebraic language used to describe and solve large-scale mathematical optimization problems.
-
A.
SCIP
SCIP is the ICAO airport code for Mataveri International Airport, the main air gateway to Easter Island in Chile.
-
B.
CVX
CVX is the stock ticker symbol for Chevron Corporation, a major American multinational energy and oil company.
-
C.
BrainScript modeling language
BrainScript modeling language is a domain-specific scripting language used to define and train neural network models within the Microsoft Cognitive Toolkit (CNTK).
-
D.
ADMM
ADMM is a regional forum that brings together the defence ministers of ASEAN member states to discuss and coordinate security and defence cooperation in Southeast Asia.
-
E.
Simulink
Simulink is a graphical modeling and simulation environment for designing, simulating, and analyzing dynamic systems, commonly used within MATLAB for control, signal processing, and embedded system development.
- F. None of above. chosen
Statements (82)
| Predicate | Object |
|---|---|
| instanceOf |
algebraic modeling language
ⓘ
mathematical optimization modeling language ⓘ |
| abbreviationFor |
A Mathematical Programming Language
ⓘ
linked to:
AMPL modeling language
|
| compatibleWith |
CBC
ⓘ
CPLEX ⓘ
linked to:
IBM Decision Optimization
GLPK ⓘ Gurobi ⓘ
linked to:
IBM Decision Optimization
IPOPT ⓘ KNITRO ⓘ MINOS ⓘ SNOPT ⓘ
linked to:
Nonlinear programming
Xpress ⓘ many commercial and open-source solvers ⓘ |
| designedFor | large-scale mathematical optimization ⓘ |
| developedBy |
Brian W. Kernighan
ⓘ
linked to:
Brian Kernighan
David M. Gay ⓘ Robert Fourer ⓘ |
| documentedIn |
AMPL: A Modeling Language for Mathematical Programming
ⓘ
linked to:
AMPL modeling language
|
| domain |
mathematical programming
ⓘ
optimization ⓘ |
| fullName |
A Mathematical Programming Language
ⓘ
linked to:
AMPL modeling language
|
| hasCompany | AMPL Optimization LLC ⓘ |
| hasComponent |
data file
ⓘ
model file ⓘ run file ⓘ |
| hasDesignGoal |
expressive algebraic modeling
ⓘ
rapid model prototyping ⓘ scalability to large problems ⓘ solver independence ⓘ |
| hasFeature |
algebraic notation for optimization models
ⓘ
automatic differentiation for nonlinear models ⓘ constraints and objective functions ⓘ data tables interface ⓘ declarative modeling style ⓘ interactive command environment ⓘ logical constraints ⓘ parameters and variables ⓘ piecewise-linear expressions ⓘ presolve and model transformations ⓘ scripting and control flow ⓘ separate model and run files ⓘ separation of model and data ⓘ set and indexing constructs ⓘ solver-independent model specification ⓘ suffixes for advanced solver options ⓘ support for external functions ⓘ support for large sparse models ⓘ support for scripting languages via APIs ⓘ |
| hasPublisher |
Brooks/Cole
ⓘ
linked to:
Cengage Learning
Duxbury Press ⓘ |
| languageParadigm | declarative ⓘ |
| licenseType | proprietary with academic licenses ⓘ |
| publishedIn | 1993 ⓘ |
| supports |
conditional expressions in models
ⓘ
indexing over sets and subsets ⓘ linear programming ⓘ mixed-integer nonlinear programming ⓘ mixed-integer programming ⓘ network optimization ⓘ nonlinear programming ⓘ piecewise-linear optimization ⓘ quadratic programming ⓘ scenario-based stochastic modeling ⓘ stochastic programming ⓘ user-defined functions via external libraries ⓘ |
| supportsDataFormat |
CSV tables
ⓘ
relational database tables via ODBC ⓘ spreadsheet tables via ODBC ⓘ |
| supportsInterface |
AMPL IDE and graphical tools
ⓘ
APIs for C ⓘ APIs for C++ ⓘ APIs for Java ⓘ APIs for Python ⓘ command-line interface ⓘ |
| usedIn |
energy systems optimization
ⓘ
finance ⓘ industrial engineering ⓘ operations research ⓘ supply chain optimization ⓘ telecommunications network design ⓘ transportation and logistics ⓘ |
| writtenIn | C ⓘ |
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.
Instruction
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.
Input
Subject: AMPL modeling language Description of subject: AMPL modeling language is a high-level algebraic language used to describe and solve large-scale mathematical optimization problems.
Referenced by (5)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject linked to:
AMPL modeling language
linked to: AMPL modeling language
subject linked to:
AMPL modeling language
linked to: AMPL modeling language
subject linked to:
AMPL modeling language
linked to: AMPL modeling language