Théorie analytique des probabilités
E139490
Théorie analytique des probabilités is Pierre-Simon Laplace’s foundational treatise that systematically developed probability theory and laid the groundwork for modern statistics.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Théorie analytique des probabilités canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T1221695 — 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: Théorie analytique des probabilités Context triple: [Pierre-Simon Laplace, notableWork, Théorie analytique des probabilités]
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A.
Théorie analytique de la chaleur
Théorie analytique de la chaleur is Joseph Fourier’s foundational 1822 treatise that introduced Fourier series and laid the mathematical groundwork for the modern theory of heat conduction and harmonic analysis.
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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.
De ratiociniis in ludo aleae
De ratiociniis in ludo aleae is a pioneering 17th-century treatise on probability theory, particularly as applied to games of chance.
-
D.
Gaussian law of error
The Gaussian law of error is a fundamental statistical principle stating that measurement errors tend to follow a normal (bell-shaped) distribution, forming the basis of much of probability theory and statistical inference.
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E.
Mémoire sur une propriété générale d’une classe très étendue de fonctions transcendantes
Mémoire sur une propriété générale d’une classe très étendue de fonctions transcendantes is a seminal mathematical paper by Niels Henrik Abel that develops fundamental results on transcendental functions and helped lay groundwork for modern analysis.
- 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: Théorie analytique des probabilités Target entity description: Théorie analytique des probabilités is Pierre-Simon Laplace’s foundational treatise that systematically developed probability theory and laid the groundwork for modern statistics.
-
A.
Théorie analytique de la chaleur
Théorie analytique de la chaleur is Joseph Fourier’s foundational 1822 treatise that introduced Fourier series and laid the mathematical groundwork for the modern theory of heat conduction and harmonic analysis.
-
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.
De ratiociniis in ludo aleae
De ratiociniis in ludo aleae is a pioneering 17th-century treatise on probability theory, particularly as applied to games of chance.
-
D.
Gaussian law of error
The Gaussian law of error is a fundamental statistical principle stating that measurement errors tend to follow a normal (bell-shaped) distribution, forming the basis of much of probability theory and statistical inference.
-
E.
Mémoire sur une propriété générale d’une classe très étendue de fonctions transcendantes
Mémoire sur une propriété générale d’une classe très étendue de fonctions transcendantes is a seminal mathematical paper by Niels Henrik Abel that develops fundamental results on transcendental functions and helped lay groundwork for modern analysis.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
book
ⓘ
mathematical treatise ⓘ |
| aim |
to apply probability to natural philosophy
ⓘ
to apply probability to social sciences ⓘ to place probability on an analytical foundation ⓘ |
| author | Pierre-Simon Laplace ⓘ |
| authorBirthYear | 1749 ⓘ |
| authorDeathYear | 1827 ⓘ |
| centuryOfPublication | 19th century ⓘ |
| countryOfOrigin | France ⓘ |
| describedAs |
foundational treatise on probability
ⓘ
systematic development of probability theory ⓘ |
| field |
mathematics
ⓘ
probability theory ⓘ statistics ⓘ |
| hasEdition |
1812 first edition
ⓘ
subsequent expanded editions ⓘ |
| hasPart | Essai philosophique sur les probabilités ⓘ |
| influenced |
19th-century probability theory
ⓘ
20th-century mathematical statistics ⓘ Bayesian statistics ⓘ
linked to:
Bayesian inference
frequency theory of probability ⓘ modern statistics ⓘ |
| method |
analytic methods
ⓘ
calculus ⓘ series expansions ⓘ |
| notableFor |
development of generating function techniques in probability
ⓘ
early formulation of Bayesian ideas ⓘ influence on later probabilists such as Poisson ⓘ systematic treatment of errors of observation ⓘ |
| originalLanguage | French ⓘ |
| placeOfPublication | Paris ⓘ |
| publicationYear | 1812 ⓘ |
| publisher | Courcier ⓘ |
| structure | multiple books and supplements ⓘ |
| topic |
Bayesian inference
ⓘ
analytical methods in probability ⓘ binomial distribution ⓘ combinatorics ⓘ error theory ⓘ expectation ⓘ foundations of probability ⓘ generating functions ⓘ inverse probability ⓘ law of large numbers ⓘ least squares ⓘ normal distribution ⓘ probability of causes ⓘ |
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: Théorie analytique des probabilités Description of subject: Théorie analytique des probabilités is Pierre-Simon Laplace’s foundational treatise that systematically developed probability theory and laid the groundwork for modern statistics.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.