Truth and Probability
E381620
Truth and Probability is a foundational 1926 essay by philosopher F. P. Ramsey that develops a subjective theory of probability and lays groundwork for modern Bayesian decision theory.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Truth and Probability canonical | 2 |
| "Truth and Probability" | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3725151 — 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: Truth and Probability Context triple: [F. P. Ramsey, notableWork, Truth and Probability]
-
A.
Logical Foundations of Probability
Logical Foundations of Probability is a seminal philosophical work by Rudolf Carnap that develops a rigorous logical and formal account of probability and inductive reasoning.
-
B.
A Treatise on Probability
A Treatise on Probability is John Maynard Keynes’s influential 1921 work that develops a logical and philosophical theory of probability, challenging classical and frequency-based interpretations.
-
C.
The Logic of Chance
The Logic of Chance is an influential 1866 book by John Venn that helped establish the frequency interpretation of probability and advanced the philosophical foundations of statistical reasoning.
-
D.
Logic: The Theory of Inquiry
Logic: The Theory of Inquiry is John Dewey’s major work on logic, presenting a pragmatic account of reasoning as an experimental, inquiry-driven process grounded in experience.
-
E.
Foundations of Probability
Foundations of Probability is a seminal textbook by mathematician Alfréd Rényi that presents a rigorous, axiomatic treatment of probability theory.
- 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: Truth and Probability Target entity description: Truth and Probability is a foundational 1926 essay by philosopher F. P. Ramsey that develops a subjective theory of probability and lays groundwork for modern Bayesian decision theory.
-
A.
Logical Foundations of Probability
Logical Foundations of Probability is a seminal philosophical work by Rudolf Carnap that develops a rigorous logical and formal account of probability and inductive reasoning.
-
B.
A Treatise on Probability
A Treatise on Probability is John Maynard Keynes’s influential 1921 work that develops a logical and philosophical theory of probability, challenging classical and frequency-based interpretations.
-
C.
The Logic of Chance
The Logic of Chance is an influential 1866 book by John Venn that helped establish the frequency interpretation of probability and advanced the philosophical foundations of statistical reasoning.
-
D.
Logic: The Theory of Inquiry
Logic: The Theory of Inquiry is John Dewey’s major work on logic, presenting a pragmatic account of reasoning as an experimental, inquiry-driven process grounded in experience.
-
E.
Foundations of Probability
Foundations of Probability is a seminal textbook by mathematician Alfréd Rényi that presents a rigorous, axiomatic treatment of probability theory.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
philosophical essay
ⓘ
work on probability theory ⓘ |
| addresses |
foundations of statistical reasoning
ⓘ
nature of rational choice under uncertainty ⓘ rational belief revision ⓘ relationship between truth and probability ⓘ |
| author |
F. P. Ramsey
ⓘ
Frank Plumpton Ramsey ⓘ
linked to:
F. P. Ramsey
|
| countryOfOrigin | United Kingdom ⓘ |
| develops |
coherence-based justification of probability axioms
ⓘ
decision-theoretic foundation for probability ⓘ representation of beliefs by probabilities ⓘ representation of preferences by utilities ⓘ subjective theory of probability ⓘ |
| field |
Bayesian probability
ⓘ
decision theory ⓘ epistemology ⓘ philosophy of probability ⓘ |
| firstPresentedAs | paper in philosophy of probability ⓘ |
| genre | academic essay ⓘ |
| hasPart |
analysis of consistency constraints on beliefs
ⓘ
derivation of probability axioms from betting behavior ⓘ discussion of logical versus subjective probability ⓘ treatment of utility and value ⓘ |
| historicalSignificance |
early formulation of subjective expected utility theory
ⓘ
foundational work for modern Bayesianism ⓘ |
| influenced |
Bayesian decision theory
ⓘ
linked to:
Bayes rules
Bayesian epistemology ⓘ Bruno de Finetti ⓘ Leonard J. Savage ⓘ modern expected utility theory ⓘ subjective Bayesianism ⓘ |
| influencedBy |
John Maynard Keynes
ⓘ
logical theory of probability ⓘ |
| language | English ⓘ |
| mainTopic |
Bayesian decision theory
ⓘ
linked to:
Bayes rules
Dutch book arguments ⓘ axiomatization of probability ⓘ coherence of beliefs ⓘ degree of belief ⓘ expected utility ⓘ subjective probability ⓘ utility theory ⓘ |
| philosophicalTradition | analytic philosophy ⓘ |
| proposes |
Dutch book argument for probability coherence
ⓘ
calibration of degrees of belief ⓘ |
| publicationYear | 1926 ⓘ |
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: Truth and Probability Description of subject: Truth and Probability is a foundational 1926 essay by philosopher F. P. Ramsey that develops a subjective theory of probability and lays groundwork for modern Bayesian decision theory.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.