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.