Isabelle/ML
E822912
Isabelle/ML is the ML-based implementation and extension language used to develop and script the Isabelle interactive theorem prover.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Isabelle/ML canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9810247 — 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: Isabelle/ML Context triple: [Markus Wenzel, notableWork, Isabelle/ML]
-
A.
Isabelle proof assistant
Isabelle proof assistant is a widely used interactive theorem prover and generic proof assistant designed for formal verification and mathematical logic, particularly known for its support of higher-order logic.
-
B.
Isabelle/HOL: A Proof Assistant for Higher-Order Logic
"Isabelle/HOL: A Proof Assistant for Higher-Order Logic" is a foundational book and system documentation that presents the Isabelle/HOL interactive theorem prover, widely used for formal verification and higher-order logic reasoning in computer science and mathematics.
-
C.
Boyer–Moore theorem prover
The Boyer–Moore theorem prover is an influential automated reasoning system for first-order logic and recursive function theory, notable for pioneering techniques in mechanical proof and program verification.
-
D.
Hoare logic
Hoare logic is a formal system in computer science used to reason rigorously about the correctness of computer programs using logical assertions about program states.
-
E.
Satisfiability Modulo Theories (SMT)
Satisfiability Modulo Theories (SMT) is a framework in computer science and mathematical logic for deciding the satisfiability of logical formulas with respect to background theories such as arithmetic, bit-vectors, arrays, and data types, widely used in verification, synthesis, and automated reasoning.
- 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: Isabelle/ML Target entity description: Isabelle/ML is the ML-based implementation and extension language used to develop and script the Isabelle interactive theorem prover.
-
A.
Isabelle proof assistant
Isabelle proof assistant is a widely used interactive theorem prover and generic proof assistant designed for formal verification and mathematical logic, particularly known for its support of higher-order logic.
-
B.
Isabelle/HOL: A Proof Assistant for Higher-Order Logic
"Isabelle/HOL: A Proof Assistant for Higher-Order Logic" is a foundational book and system documentation that presents the Isabelle/HOL interactive theorem prover, widely used for formal verification and higher-order logic reasoning in computer science and mathematics.
-
C.
Boyer–Moore theorem prover
The Boyer–Moore theorem prover is an influential automated reasoning system for first-order logic and recursive function theory, notable for pioneering techniques in mechanical proof and program verification.
-
D.
Hoare logic
Hoare logic is a formal system in computer science used to reason rigorously about the correctness of computer programs using logical assertions about program states.
-
E.
Satisfiability Modulo Theories (SMT)
Satisfiability Modulo Theories (SMT) is a framework in computer science and mathematical logic for deciding the satisfiability of logical formulas with respect to background theories such as arithmetic, bit-vectors, arrays, and data types, widely used in verification, synthesis, and automated reasoning.
- F. None of above. chosen
Statements (50)
| Predicate | Object |
|---|---|
| instanceOf |
extension language
ⓘ
implementation language ⓘ programming language ⓘ |
| basedOn | Standard ML NERFINISHED ⓘ |
| category |
domain-specific extension of Standard ML
ⓘ
theorem prover implementation language ⓘ |
| designedFor | tight integration with the Isabelle logical environment ⓘ |
| documentedIn | Isabelle/Isar Implementation manual NERFINISHED ⓘ |
| executedIn |
Isabelle/ML runtime environment
NERFINISHED
ⓘ
JVM-based Isabelle process in recent Isabelle versions ⓘ |
| extends |
Standard ML with Isabelle-specific libraries
ⓘ
Standard ML with Isabelle-specific syntax support ⓘ Standard ML with logical infrastructure access ⓘ |
| hasFeature |
access to Isabelle context data
ⓘ
antiquotations for embedding ML in Isar ⓘ exception handling ⓘ higher-order functions ⓘ interfaces to external tools via Isabelle infrastructure ⓘ module system from Standard ML ⓘ parallel and asynchronous programming support via Isabelle runtime ⓘ pattern matching ⓘ quasi-quotations for logical entities ⓘ static type system ⓘ tailored libraries for terms and types ⓘ |
| integratedWith |
Isabelle code generator infrastructure
NERFINISHED
ⓘ
Isabelle proof context ⓘ Isabelle term representation ⓘ Isabelle theory context ⓘ Isabelle type system ⓘ Isabelle/Isar NERFINISHED ⓘ |
| maintainedBy | Isabelle development team NERFINISHED ⓘ |
| primaryAuthor | Makarius Wenzel NERFINISHED ⓘ |
| provides |
APIs for defining new attributes
ⓘ
APIs for defining new commands ⓘ APIs for defining new proof methods ⓘ APIs for manipulating Isabelle terms ⓘ APIs for manipulating Isabelle theories ⓘ APIs for manipulating Isabelle types ⓘ APIs for manipulating proof states ⓘ |
| usedBy |
Isabelle tool developers
ⓘ
advanced Isabelle users ⓘ |
| usedFor |
developing the Isabelle theorem prover
ⓘ
extending the Isabelle system ⓘ implementing Isabelle attributes ⓘ implementing Isabelle methods ⓘ implementing Isabelle proof tools ⓘ implementing Isabelle tactics ⓘ implementing proof procedures in Isabelle ⓘ scripting Isabelle tools ⓘ |
| usedIn | Isabelle NERFINISHED ⓘ |
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: Isabelle/ML Description of subject: Isabelle/ML is the ML-based implementation and extension language used to develop and script the Isabelle interactive theorem prover.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.