Turing test
E78810
benchmark in artificial intelligence
imitation game
philosophical thought experiment
test of machine intelligence
The Turing test is a benchmark in artificial intelligence that evaluates a machine's ability to exhibit human-like intelligence by determining whether its responses are indistinguishable from those of a human in conversation.
All labels observed (4)
| Label | Occurrences |
|---|---|
| Turing test canonical | 10 |
| Reverse Turing test | 1 |
| Total Turing test | 1 |
| Turing test proposal | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T629498 — 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: Turing test Context triple: [Alan Turing, knownFor, Turing test]
-
A.
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.
-
B.
AlphaGo
AlphaGo is an artificial intelligence program developed by DeepMind that became famous for defeating world champion Go players using deep neural networks and reinforcement learning.
-
C.
AlphaStar
AlphaStar is a DeepMind-created artificial intelligence system that achieved grandmaster-level performance in the real-time strategy game StarCraft II.
-
D.
Church–Turing thesis
The Church–Turing thesis is a foundational principle in computability theory stating that any function that can be effectively computed by an algorithm can be computed by a Turing machine (or equivalently by other formal models of computation).
-
E.
AlphaZero
AlphaZero is a DeepMind-developed artificial intelligence system that mastered complex games like chess, shogi, and Go through self-play reinforcement learning without human-crafted strategies.
- 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: Turing test Target entity description: The Turing test is a benchmark in artificial intelligence that evaluates a machine's ability to exhibit human-like intelligence by determining whether its responses are indistinguishable from those of a human in conversation.
-
A.
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.
-
B.
AlphaGo
AlphaGo is an artificial intelligence program developed by DeepMind that became famous for defeating world champion Go players using deep neural networks and reinforcement learning.
-
C.
AlphaStar
AlphaStar is a DeepMind-created artificial intelligence system that achieved grandmaster-level performance in the real-time strategy game StarCraft II.
-
D.
Church–Turing thesis
The Church–Turing thesis is a foundational principle in computability theory stating that any function that can be effectively computed by an algorithm can be computed by a Turing machine (or equivalently by other formal models of computation).
-
E.
AlphaZero
AlphaZero is a DeepMind-developed artificial intelligence system that mastered complex games like chess, shogi, and Go through self-play reinforcement learning without human-crafted strategies.
- F. None of above. chosen
Statements (50)
| Predicate | Object |
|---|---|
| instanceOf |
benchmark in artificial intelligence
ⓘ
imitation game ⓘ philosophical thought experiment ⓘ test of machine intelligence ⓘ |
| approach | black-box behavioral assessment ⓘ |
| coreConcept |
behavioral definition of intelligence
ⓘ
imitation of human conversational behavior ⓘ |
| creator | Alan Turing ⓘ |
| criticizedFor |
anthropocentric definition of intelligence
ⓘ
focus on deception rather than understanding ⓘ insufficient as a comprehensive test of intelligence ⓘ narrow focus on linguistic behavior ⓘ |
| describedIn | Computing Machinery and Intelligence ⓘ |
| doesNotRequire | inspection of internal mechanisms ⓘ |
| evaluationMethod |
natural language conversation
ⓘ
text-based dialogue ⓘ |
| field |
artificial intelligence
ⓘ
cognitive science ⓘ philosophy of artificial intelligence ⓘ philosophy of mind ⓘ |
| hasVariant |
Loebner Prize
ⓘ
surface form:
Loebner Prize Turing test
Turing test self-linksurface differs ⓘ
surface form:
Reverse Turing test
Turing test self-linksurface differs ⓘ
surface form:
Total Turing test
Visual Turing test ⓘ |
| historicalSignificance | one of the earliest formal proposals for testing machine intelligence ⓘ |
| inception | 1950 ⓘ |
| influenced |
AI evaluation methodologies
ⓘ
chatbot research ⓘ development of conversational agents ⓘ |
| inspired | Loebner Prize ⓘ |
| interactionMedium |
computer terminal
ⓘ
text-only communication ⓘ |
| involves |
human interlocutor
ⓘ
human judge ⓘ machine interlocutor ⓘ |
| keyCriterion | indistinguishability from human responses ⓘ |
| language | English (original formulation) ⓘ |
| namedAfter | Alan Turing ⓘ |
| primaryGoal | evaluate a machine's ability to exhibit human-like intelligence ⓘ |
| proposedQuestion | Can machines think? ⓘ |
| publicationYear | 1950 ⓘ |
| publishedIn |
Mind
ⓘ
surface form:
Mind (journal)
|
| relatedConcept |
CAPTCHA
ⓘ
Chinese Room ⓘ
surface form:
Chinese room argument
imitation game ⓘ machine consciousness ⓘ strong AI ⓘ weak AI ⓘ |
| successCondition |
judge cannot reliably distinguish machine from human
ⓘ
machine is misidentified as human sufficiently often ⓘ |
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: Turing test Description of subject: The Turing test is a benchmark in artificial intelligence that evaluates a machine's ability to exhibit human-like intelligence by determining whether its responses are indistinguishable from those of a human in conversation.
Referenced by (13)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Total Turing test
this entity surface form:
Reverse Turing test
this entity surface form:
Turing test proposal
subject surface form:
Imitation Game
subject surface form:
Imitation Game