Triple

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).

Phrase: Lévy–Khintchine formula | Statement: [Paul Lévy, knownFor, Lévy–Khintchine formula]

Target entity: Lévy–Khintchine formula
Context triple: [Paul Lévy, knownFor, Lévy–Khintchine formula]

• A. Khinchin–Pollaczek formula
  The Khinchin–Pollaczek formula is a result in probability theory and queueing theory that provides an explicit expression for the stationary waiting-time distribution in certain single-server queues.
• B. Feynman–Kac formula
  The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
• C. Clark–Ocone formula
  The Clark–Ocone formula is a key result in stochastic calculus and Malliavin calculus that provides an explicit integral representation of square-integrable random variables with respect to Brownian motion.
• D. Bochner theorem on characteristic functions
  The Bochner theorem on characteristic functions is a fundamental result in probability theory and harmonic analysis that characterizes which functions are Fourier transforms of probability measures by requiring them to be positive-definite, continuous, and normalized at zero.
• E. Dynkin formula
  Dynkin formula is a fundamental result in the theory of Markov processes that expresses the expected value of a function of the process at a stopping time in terms of its generator and an integral over time.
• F. None of above. chosen
• G. Unsure - the case is ambiguous/there is not enough information to decide.

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]"

Entity: Lévy–Khintchine formula
Triple: [Paul Lévy, knownFor, Lévy–Khintchine formula]

The Lévy–Khintchine formula is a fundamental result in probability theory that characterizes the characteristic functions of infinitely divisible distributions via a canonical decomposition involving a drift term, a Gaussian component, and a Lévy measure.

Target entity: Lévy–Khintchine formula
Target entity description: The Lévy–Khintchine formula is a fundamental result in probability theory that characterizes the characteristic functions of infinitely divisible distributions via a canonical decomposition involving a drift term, a Gaussian component, and a Lévy measure.

• A. Khinchin–Pollaczek formula
  The Khinchin–Pollaczek formula is a result in probability theory and queueing theory that provides an explicit expression for the stationary waiting-time distribution in certain single-server queues.
• B. Feynman–Kac formula
  The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
• C. Clark–Ocone formula
  The Clark–Ocone formula is a key result in stochastic calculus and Malliavin calculus that provides an explicit integral representation of square-integrable random variables with respect to Brownian motion.
• D. Bochner theorem on characteristic functions chosen
  The Bochner theorem on characteristic functions is a fundamental result in probability theory and harmonic analysis that characterizes which functions are Fourier transforms of probability measures by requiring them to be positive-definite, continuous, and normalized at zero.
• E. Dynkin formula
  Dynkin formula is a fundamental result in the theory of Markov processes that expresses the expected value of a function of the process at a stopping time in terms of its generator and an integral over time.
• F. None of above.