Electronic Journal of Probability
E833562
The Electronic Journal of Probability is a peer-reviewed open-access mathematical journal focusing on probability theory and related fields.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Electronic Journal of Probability canonical | 3 |
How this entity was disambiguated
This entity first appeared as the object of triple T9986338 — 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: Electronic Journal of Probability Context triple: [Institute of Mathematical Statistics, hasJournal, Electronic Journal of Probability]
-
A.
Modern Probability Theory and Its Applications
"Modern Probability Theory and Its Applications" is a foundational textbook by Emanuel Parzen that systematically develops modern probability theory and demonstrates its use in a wide range of statistical and applied contexts.
-
B.
The Theory of Probability
The Theory of Probability is Hans Reichenbach’s influential philosophical and mathematical treatise that helped establish a rigorous, frequency-based interpretation of probability within the logical empiricist tradition.
-
C.
Electronic Research Announcements of the American Mathematical Society
Electronic Research Announcements of the American Mathematical Society is a peer-reviewed mathematical journal that rapidly disseminates brief, significant research results across all areas of mathematics.
-
D.
Institute of Mathematical Statistics
The Institute of Mathematical Statistics is a leading international professional society dedicated to the development and dissemination of theory and applications in statistics and probability.
-
E.
Isserlis’ theorem in probability theory
Isserlis’ theorem in probability theory is a result that expresses higher-order moments of jointly Gaussian random variables in terms of sums of products of their pairwise covariances.
- 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: Electronic Journal of Probability Target entity description: The Electronic Journal of Probability is a peer-reviewed open-access mathematical journal focusing on probability theory and related fields.
-
A.
Modern Probability Theory and Its Applications
"Modern Probability Theory and Its Applications" is a foundational textbook by Emanuel Parzen that systematically develops modern probability theory and demonstrates its use in a wide range of statistical and applied contexts.
-
B.
The Theory of Probability
The Theory of Probability is Hans Reichenbach’s influential philosophical and mathematical treatise that helped establish a rigorous, frequency-based interpretation of probability within the logical empiricist tradition.
-
C.
Electronic Research Announcements of the American Mathematical Society
Electronic Research Announcements of the American Mathematical Society is a peer-reviewed mathematical journal that rapidly disseminates brief, significant research results across all areas of mathematics.
-
D.
Institute of Mathematical Statistics
The Institute of Mathematical Statistics is a leading international professional society dedicated to the development and dissemination of theory and applications in statistics and probability.
-
E.
Isserlis’ theorem in probability theory
Isserlis’ theorem in probability theory is a result that expresses higher-order moments of jointly Gaussian random variables in terms of sums of products of their pairwise covariances.
- F. None of above. chosen
Statements (24)
| Predicate | Object |
|---|---|
| instanceOf |
academic journal
ⓘ
open-access journal ⓘ |
| academicDiscipline |
mathematics
ⓘ
probability theory ⓘ stochastic processes ⓘ |
| accessModel | open access ⓘ |
| hasAbbreviation | EJP ⓘ |
| hasArticleType |
research article
ⓘ
short communication ⓘ survey article ⓘ |
| hasCategory |
Mathematics journals
ⓘ
Open access journals ⓘ Probability journals ⓘ |
| hasMedium | online ⓘ |
| hasSisterJournal | Electronic Communications in Probability ⓘ |
| language | English ⓘ |
| licensePolicy |
authors retain copyright
ⓘ
free access for readers ⓘ |
| publicationFormat | electronic ⓘ |
| publishingModel | online-only ⓘ |
| reviewProcess | peer reviewed ⓘ |
| subjectArea |
probability theory
ⓘ
statistics ⓘ stochastic analysis ⓘ |
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: Electronic Journal of Probability Description of subject: The Electronic Journal of Probability is a peer-reviewed open-access mathematical journal focusing on probability theory and related fields.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.