Jerzy Neyman
E668387
Jerzy Neyman was a pioneering Polish statistician best known for developing the Neyman–Pearson lemma and foundational concepts of hypothesis testing and confidence intervals.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Jerzy Neyman canonical | 10 |
How this entity was disambiguated
This entity first appeared as the object of triple T7454050 — 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.
Target entity: Jerzy Neyman Context triple: [Karl Pearson, influenced, Jerzy Neyman]
-
A.
Egon Pearson
Egon Pearson was a British statistician best known for co-developing the Neyman–Pearson lemma, a fundamental result in hypothesis testing.
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B.
William Kruskal
William Kruskal was an American statistician best known for co-developing the Kruskal–Wallis test, a nonparametric method for comparing multiple groups.
-
C.
Carl-Gustav Esseen
Carl-Gustav Esseen was a Swedish mathematician best known for his contributions to probability theory, particularly his work on the Berry–Esseen theorem quantifying the rate of convergence in the central limit theorem.
-
D.
Richard von Mises
Richard von Mises was an Austrian-American mathematician and physicist known for his foundational work in probability theory, aerodynamics, and the philosophy of science.
-
E.
Solomon Kullback
Solomon Kullback was an American statistician and cryptanalyst best known for co-developing the Kullback–Leibler divergence, a fundamental concept in information theory and statistics.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Jerzy Neyman Target entity description: Jerzy Neyman was a pioneering Polish statistician best known for developing the Neyman–Pearson lemma and foundational concepts of hypothesis testing and confidence intervals.
-
A.
Egon Pearson
Egon Pearson was a British statistician best known for co-developing the Neyman–Pearson lemma, a fundamental result in hypothesis testing.
-
B.
William Kruskal
William Kruskal was an American statistician best known for co-developing the Kruskal–Wallis test, a nonparametric method for comparing multiple groups.
-
C.
Carl-Gustav Esseen
Carl-Gustav Esseen was a Swedish mathematician best known for his contributions to probability theory, particularly his work on the Berry–Esseen theorem quantifying the rate of convergence in the central limit theorem.
-
D.
Richard von Mises
Richard von Mises was an Austrian-American mathematician and physicist known for his foundational work in probability theory, aerodynamics, and the philosophy of science.
-
E.
Solomon Kullback
Solomon Kullback was an American statistician and cryptanalyst best known for co-developing the Kullback–Leibler divergence, a fundamental concept in information theory and statistics.
- F. None of above. chosen
Statements (50)
| Predicate | Object |
|---|---|
| instanceOf |
human
ⓘ
mathematician ⓘ statistician ⓘ university teacher ⓘ |
| academicAdvisor | Sergei Natanovich Bernstein NERFINISHED ⓘ |
| awardReceived |
Guy Medal in Gold
NERFINISHED
ⓘ
Honorary doctorate from the University of Chicago ⓘ Honorary doctorate from the University of Warsaw ⓘ U.S. National Medal of Science NERFINISHED ⓘ |
| countryOfCitizenship |
Poland
ⓘ
United States of America ⓘ |
| dateOfBirth | 1894-04-16 ⓘ |
| dateOfDeath | 1981-08-05 ⓘ |
| educatedAt |
University of Kharkiv
NERFINISHED
ⓘ
University of Paris NERFINISHED ⓘ University of Warsaw NERFINISHED ⓘ |
| employer |
University of California, Berkeley
ⓘ
University of London NERFINISHED ⓘ University of Warsaw NERFINISHED ⓘ |
| familyName | Neyman NERFINISHED ⓘ |
| fieldOfWork |
probability theory
ⓘ
statistics ⓘ |
| givenName | Jerzy NERFINISHED ⓘ |
| influenced |
development of confidence interval methodology
ⓘ
modern hypothesis testing theory ⓘ |
| knownFor |
confidence intervals
ⓘ
frequentist statistics ⓘ hypothesis testing ⓘ sequential analysis ⓘ |
| languagesSpokenWrittenOrSigned |
English
ⓘ
French ⓘ Polish ⓘ Russian ⓘ |
| memberOf |
American Academy of Arts and Sciences
ⓘ
National Academy of Sciences ⓘ
surface form:
National Academy of Sciences of the United States of America
Polish Academy of Learning NERFINISHED ⓘ |
| movement | frequentist school of statistics ⓘ |
| nativeLanguage | Polish ⓘ |
| notableWork |
Neyman construction
NERFINISHED
ⓘ
Neyman–Pearson lemma NERFINISHED ⓘ Neyman–Scott problem NERFINISHED ⓘ confidence interval theory ⓘ |
| placeOfBirth |
Bendery
NERFINISHED
ⓘ
Bessarabia Governorate NERFINISHED ⓘ |
| placeOfDeath | Oakland, California NERFINISHED ⓘ |
| positionHeld |
founding director of the Statistical Laboratory at UC Berkeley
ⓘ
professor of statistics ⓘ |
| sexOrGender | male ⓘ |
| workLocation |
Berkeley, California
NERFINISHED
ⓘ
London, England ⓘ
surface form:
London
|
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.
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.
Subject: Jerzy Neyman Description of subject: Jerzy Neyman was a pioneering Polish statistician best known for developing the Neyman–Pearson lemma and foundational concepts of hypothesis testing and confidence intervals.
Referenced by (10)
Full triples — surface form annotated when it differs from this entity's canonical label.