Glushkov construction
E632952
Glushkov construction is a method in automata theory that converts a regular expression into an equivalent nondeterministic finite automaton with a specific position-based structure.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Glushkov construction canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T6991417 — 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: Glushkov construction Context triple: [Thompson's algorithm for regular expression matching, relatedTo, Glushkov construction]
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A.
Böhm–Jacopini theorem
The Böhm–Jacopini theorem is a foundational result in computer science stating that any computer program can be written using only sequence, selection, and iteration constructs, without requiring goto statements.
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B.
Turing machine
A Turing machine is an abstract computational model that manipulates symbols on an infinite tape according to a set of rules, providing a formal foundation for the concept of algorithm and computability.
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C.
Kleene
Kleene is a surname most notably associated with American mathematician Stephen Kleene, a pioneer in recursion theory and mathematical logic.
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D.
Kleene algebra
Kleene algebra is an algebraic structure used to model and reason about regular expressions, program control flow, and formal languages through operations like choice, sequencing, and iteration.
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E.
Landin’s SECD machine
Landin’s SECD machine is an early abstract machine for functional programming languages that introduced a systematic model for evaluating expressions using a stack, environment, control, and dump.
- 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: Glushkov construction Target entity description: Glushkov construction is a method in automata theory that converts a regular expression into an equivalent nondeterministic finite automaton with a specific position-based structure.
-
A.
Böhm–Jacopini theorem
The Böhm–Jacopini theorem is a foundational result in computer science stating that any computer program can be written using only sequence, selection, and iteration constructs, without requiring goto statements.
-
B.
Turing machine
A Turing machine is an abstract computational model that manipulates symbols on an infinite tape according to a set of rules, providing a formal foundation for the concept of algorithm and computability.
-
C.
Kleene
Kleene is a surname most notably associated with American mathematician Stephen Kleene, a pioneer in recursion theory and mathematical logic.
-
D.
Kleene algebra
Kleene algebra is an algebraic structure used to model and reason about regular expressions, program control flow, and formal languages through operations like choice, sequencing, and iteration.
-
E.
Landin’s SECD machine
Landin’s SECD machine is an early abstract machine for functional programming languages that introduced a systematic model for evaluating expressions using a stack, environment, control, and dump.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
automata theory construction method
ⓘ
formal language theory concept ⓘ |
| alsoKnownAs |
position automata method
ⓘ
position automaton construction ⓘ position-based NFA construction NERFINISHED ⓘ |
| application |
conversion of regular expressions to automata in compilers
ⓘ
implementation of regular expression matchers ⓘ theoretical analysis of regular languages ⓘ |
| assumes | regular expression over a finite alphabet ⓘ |
| category | construction of automata from regular expressions ⓘ |
| comparedTo |
Thompson construction uses ε-transitions while Glushkov construction does not
ⓘ
position automaton is often more compact than Thompson NFA for the same regular expression ⓘ |
| complexity | polynomial-time in the size of the regular expression ⓘ |
| defines |
a state for each occurrence of an alphabet symbol in the regular expression
ⓘ
accepting states based on last positions of the regular expression ⓘ transitions based on the follow-position relation ⓘ |
| field |
automata theory
ⓘ
formal language theory ⓘ |
| formalizes | a direct correspondence between regex symbol positions and NFA states ⓘ |
| goal | convert a regular expression into an equivalent NFA ⓘ |
| guarantees | language equivalence between the regular expression and the constructed NFA ⓘ |
| historicalContext | introduced in the 1960s ⓘ |
| influenced | later work on position-based automata ⓘ |
| inputType | regular expression ⓘ |
| isPartOf | the theory of regular languages ⓘ |
| namedAfter | Victor M. Glushkov NERFINISHED ⓘ |
| outputType |
nondeterministic finite automaton
ⓘ
ε-free NFA ⓘ |
| producesAutomatonWith |
a unique initial state
ⓘ
no ε-transitions ⓘ states corresponding to positions of symbols in the regular expression ⓘ transition structure derived from symbol positions ⓘ |
| property |
avoids ε-transitions by design
ⓘ
constructs an automaton whose number of states equals the number of symbol occurrences plus one ⓘ structurally reflects the syntax of the regular expression ⓘ |
| relatedTo |
Brzozowski derivative construction
NERFINISHED
ⓘ
McNaughton–Yamada construction NERFINISHED ⓘ Thompson construction NERFINISHED ⓘ finite automaton minimization ⓘ position automaton ⓘ |
| typicalOutputAutomaton | position automaton of the given regular expression ⓘ |
| usedIn |
design of pattern matching algorithms
ⓘ
formal verification of systems specified by regular expressions ⓘ symbolic model checking of regular properties ⓘ |
| usesConcept |
first-position set of a regular expression
ⓘ
follow-position relation ⓘ last-position set of a regular expression ⓘ position of symbol in regular expression ⓘ |
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: Glushkov construction Description of subject: Glushkov construction is a method in automata theory that converts a regular expression into an equivalent nondeterministic finite automaton with a specific position-based structure.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.