Foundations of Probability
E205767
Foundations of Probability is a seminal textbook by mathematician Alfréd Rényi that presents a rigorous, axiomatic treatment of probability theory.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Foundations of Probability canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1819309 — 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: Foundations of Probability Context triple: [Alfréd Rényi, notableWork, Foundations of 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.
Probability Theory
Probability Theory is a foundational branch of mathematics that studies random phenomena and quantifies uncertainty using concepts such as probability measures, random variables, and distributions.
-
C.
Probability and Related Topics in Physical Sciences
"Probability and Related Topics in Physical Sciences" is a classic book by mathematician Mark Kac that introduces and applies probabilistic methods to problems in physics and related scientific fields.
-
D.
Wahrscheinlichkeitslehre
Wahrscheinlichkeitslehre is a foundational work in the philosophy and axiomatization of probability theory by Hans Reichenbach, influential in both mathematics and logical empiricism.
-
E.
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.
- 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: Foundations of Probability Target entity description: Foundations of Probability is a seminal textbook by mathematician Alfréd Rényi that presents a rigorous, axiomatic treatment of probability 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.
Probability Theory
Probability Theory is a foundational branch of mathematics that studies random phenomena and quantifies uncertainty using concepts such as probability measures, random variables, and distributions.
-
C.
Probability and Related Topics in Physical Sciences
"Probability and Related Topics in Physical Sciences" is a classic book by mathematician Mark Kac that introduces and applies probabilistic methods to problems in physics and related scientific fields.
-
D.
Wahrscheinlichkeitslehre
Wahrscheinlichkeitslehre is a foundational work in the philosophy and axiomatization of probability theory by Hans Reichenbach, influential in both mathematics and logical empiricism.
-
E.
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.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
book
ⓘ
mathematics book ⓘ textbook ⓘ |
| academicDiscipline |
probability theory
ⓘ
statistics ⓘ |
| approach |
axiomatic
ⓘ
measure-theoretic ⓘ rigorous ⓘ |
| author | Alfréd Rényi ⓘ |
| field |
mathematics
ⓘ
probability theory ⓘ |
| genre |
mathematics textbook
ⓘ
scientific monograph ⓘ |
| hasPart |
appendices on measure theory
ⓘ
chapters on conditional probability and independence ⓘ chapters on convergence of random variables ⓘ chapters on expectation ⓘ chapters on limit theorems ⓘ chapters on probability spaces ⓘ chapters on random variables ⓘ |
| influencedBy | Andrey Kolmogorov's axiomatization of probability ⓘ |
| intendedAudience |
advanced undergraduates in mathematics
ⓘ
graduate students in mathematics ⓘ researchers in probability theory ⓘ |
| language | English ⓘ |
| notableFor |
clarity of exposition
ⓘ
influence on modern probability theory ⓘ rigorous axiomatic treatment of probability theory ⓘ |
| originalLanguage | Hungarian ⓘ |
| subject |
Kolmogorov axioms
ⓘ
axiomatic probability theory ⓘ conditional probability ⓘ foundations of probability ⓘ independence ⓘ laws of large numbers ⓘ limit theorems ⓘ measure-theoretic probability ⓘ probability spaces ⓘ random variables ⓘ |
| topic |
Borel sets and measurable functions
ⓘ
central limit theorem ⓘ conditional expectation ⓘ distribution functions ⓘ expectation and moments ⓘ probability as a measure on a sigma-algebra ⓘ strong law of large numbers ⓘ |
| usedIn |
graduate programs in mathematics
ⓘ
university courses on probability theory ⓘ |
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: Foundations of Probability Description of subject: Foundations of Probability is a seminal textbook by mathematician Alfréd Rényi that presents a rigorous, axiomatic treatment of probability theory.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.