complexity class EXPTIME
E679188
EXPTIME is a computational complexity class consisting of decision problems that can be solved by a deterministic Turing machine in exponential time with respect to the size of the input.
All labels observed (1)
| Label | Occurrences |
|---|---|
| complexity class EXPTIME canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7666902 — 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: complexity class EXPTIME Context triple: [Complexity Theory, defines, complexity class EXPTIME]
-
A.
NP-completeness
NP-completeness is a central concept in computational complexity theory that classifies decision problems believed to be among the hardest in NP, such that a polynomial-time solution to any one of them would yield polynomial-time solutions to all problems in NP.
-
B.
Cook–Levin theorem
The Cook–Levin theorem is a foundational result in computational complexity theory that established the Boolean satisfiability problem (SAT) as the first NP-complete problem, launching the theory of NP-completeness.
-
C.
Complexity Theory
Complexity Theory is a branch of theoretical computer science that studies the resources, such as time and space, required to solve computational problems and classifies these problems based on their inherent difficulty.
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D.
MIP equals NEXP
MIP equals NEXP is a landmark complexity-theoretic result showing that problems solvable by multi-prover interactive proofs exactly match those solvable in nondeterministic exponential time.
-
E.
Blum–Shub–Smale model of computation
The Blum–Shub–Smale model of computation is a theoretical framework for analyzing algorithms over real numbers, extending classical complexity theory beyond discrete computation.
- 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: complexity class EXPTIME Target entity description: EXPTIME is a computational complexity class consisting of decision problems that can be solved by a deterministic Turing machine in exponential time with respect to the size of the input.
-
A.
NP-completeness
NP-completeness is a central concept in computational complexity theory that classifies decision problems believed to be among the hardest in NP, such that a polynomial-time solution to any one of them would yield polynomial-time solutions to all problems in NP.
-
B.
Cook–Levin theorem
The Cook–Levin theorem is a foundational result in computational complexity theory that established the Boolean satisfiability problem (SAT) as the first NP-complete problem, launching the theory of NP-completeness.
-
C.
Complexity Theory
Complexity Theory is a branch of theoretical computer science that studies the resources, such as time and space, required to solve computational problems and classifies these problems based on their inherent difficulty.
-
D.
MIP equals NEXP
MIP equals NEXP is a landmark complexity-theoretic result showing that problems solvable by multi-prover interactive proofs exactly match those solvable in nondeterministic exponential time.
-
E.
Blum–Shub–Smale model of computation
The Blum–Shub–Smale model of computation is a theoretical framework for analyzing algorithms over real numbers, extending classical complexity theory beyond discrete computation.
- F. None of above. chosen
Statements (51)
| Predicate | Object |
|---|---|
| instanceOf |
complexity class
ⓘ
time complexity class ⓘ |
| alternativeNotation | DTIME(2^{poly(n)}) ⓘ |
| assumes | deterministic computation model ⓘ |
| believedToBeProperSupersetOf |
NP
ⓘ
P ⓘ PSPACE NERFINISHED ⓘ |
| characterizedBy | deterministic exponential time algorithms ⓘ |
| closedUnder |
complement
ⓘ
intersection ⓘ polynomial-time many-one reductions ⓘ union ⓘ |
| contains |
NP
ⓘ
P ⓘ PSPACE ⓘ |
| containsCompleteProblem |
certain two-player perfect-information games with polynomially bounded length
ⓘ
generalized checkers ⓘ generalized chess on n×n board ⓘ succinct circuit value problem ⓘ word problem for some finitely presented groups ⓘ |
| contrastWith |
EXPSPACE (exponential space)
NERFINISHED
ⓘ
NP (nondeterministic polynomial time) NERFINISHED ⓘ P (polynomial time) NERFINISHED ⓘ |
| definedBy | time-constructible bounds 2^{p(n)} ⓘ |
| definedOver | decision problems ⓘ |
| formalDefinition | set of decision problems solvable in time 2^{p(n)} for some polynomial p ⓘ |
| formalNotation | EXPTIME NERFINISHED ⓘ |
| fullName | exponential time ⓘ |
| generalizationOf | polynomial-time solvable problems ⓘ |
| hasCompleteProblemsUnder | polynomial-time many-one reductions ⓘ |
| hasResource | time ⓘ |
| introducedInField | computational complexity theory ⓘ |
| knownSeparation | P is strictly contained in EXPTIME under standard time hierarchy theorem assumptions ⓘ |
| machineModel | deterministic Turing machine ⓘ |
| notCharacterizedBy | space bounds ⓘ |
| relatedHierarchy | P ⊆ NP ⊆ PSPACE ⊆ EXPTIME ⊆ EXPSPACE ⓘ |
| relationshipStatusWithNP | NP vs EXPTIME is open ⓘ |
| relationshipStatusWithP | P vs EXPTIME is open ⓘ |
| relationshipStatusWithPSPACE | PSPACE vs EXPTIME is open ⓘ |
| studiedIn | theory of algorithms ⓘ |
| subsetOf | EXPSPACE ⓘ |
| supersetOf |
NP
ⓘ
P ⓘ PSPACE NERFINISHED ⓘ |
| timeBoundType | exponential time ⓘ |
| timeComplexityForm | O(2^{p(n)}) for some polynomial p ⓘ |
| typicalProblemDomain |
generalized board games
ⓘ
succinctly represented state spaces ⓘ |
| typicalRunningTimeForm | 2^{n^k} for some constant k ⓘ |
| upperBoundFor | problems solvable by exhaustive search over exponentially many configurations ⓘ |
| usedFor | classifying intractable decision problems ⓘ |
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: complexity class EXPTIME Description of subject: EXPTIME is a computational complexity class consisting of decision problems that can be solved by a deterministic Turing machine in exponential time with respect to the size of the input.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.