Triple
T13070789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Lévy |
E329449
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
Lévy processes
Lévy processes are a class of stochastic processes with stationary, independent increments that generalize random walks and Brownian motion, widely used to model jump-like and continuous-time random phenomena in probability theory and finance.
|
E1020434
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lévy processes | Statement: [Paul Lévy, knownFor, Lévy processes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lévy processes Context triple: [Paul Lévy, knownFor, Lévy processes]
-
A.
Itô processes
Itô processes are a class of stochastic processes, typically modeled as solutions to stochastic differential equations, that form the fundamental objects of study in Itô calculus and modern stochastic analysis.
-
B.
Stochastic Processes
"Stochastic Processes" is a foundational textbook by Emanuel Parzen that rigorously introduces the theory and applications of random processes in probability and statistics.
-
C.
Stochastic Processes
Stochastic Processes is a foundational 1953 monograph by Joseph L. Doob that rigorously develops the theory of stochastic processes and modern probability using measure-theoretic methods.
-
D.
Markov processes
Markov processes are stochastic processes in which the future evolution depends only on the present state and not on the past history.
-
E.
Lyons' rough path theory
Lyons' rough path theory is a mathematical framework that extends classical calculus to analyze and solve differential equations driven by highly irregular signals, such as paths with low regularity or stochastic processes like Brownian motion.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lévy processes Triple: [Paul Lévy, knownFor, Lévy processes]
Generated description
Lévy processes are a class of stochastic processes with stationary, independent increments that generalize random walks and Brownian motion, widely used to model jump-like and continuous-time random phenomena in probability theory and finance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lévy processes Target entity description: Lévy processes are a class of stochastic processes with stationary, independent increments that generalize random walks and Brownian motion, widely used to model jump-like and continuous-time random phenomena in probability theory and finance.
-
A.
Itô processes
Itô processes are a class of stochastic processes, typically modeled as solutions to stochastic differential equations, that form the fundamental objects of study in Itô calculus and modern stochastic analysis.
-
B.
Stochastic Processes
"Stochastic Processes" is a foundational textbook by Emanuel Parzen that rigorously introduces the theory and applications of random processes in probability and statistics.
-
C.
Stochastic Processes
Stochastic Processes is a foundational 1953 monograph by Joseph L. Doob that rigorously develops the theory of stochastic processes and modern probability using measure-theoretic methods.
-
D.
Markov processes
Markov processes are stochastic processes in which the future evolution depends only on the present state and not on the past history.
-
E.
Lyons' rough path theory
Lyons' rough path theory is a mathematical framework that extends classical calculus to analyze and solve differential equations driven by highly irregular signals, such as paths with low regularity or stochastic processes like Brownian motion.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ee6130819095d835e7ff6a8c5b |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d60510dc81909e0cba8b63a50d9c |
completed | May 3, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69f6dbb4b8848190825102be81ff693a |
completed | May 3, 2026, 5:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6dc705f28819087e5d374f83d3acc |
completed | May 3, 2026, 5:26 a.m. |
Created at: April 9, 2026, 9 p.m.