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: Gaussian moment theorem | Statement: [Isserlis’ theorem, alsoKnownAs, Gaussian moment theorem]

Target entity: Gaussian moment theorem
Context triple: [Isserlis’ theorem, alsoKnownAs, Gaussian moment theorem]

• A. Isserlis’ theorem in probability theory chosen
  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.
• B. Cramér–Wold theorem
  The Cramér–Wold theorem is a fundamental result in probability theory stating that a multivariate distribution is uniquely determined by the distributions of all its one-dimensional linear projections.
• C. Berry–Esseen theorem
  The Berry–Esseen theorem is a quantitative refinement of the central limit theorem that provides explicit bounds on the rate of convergence of normalized sums of independent random variables to the normal distribution.
• 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. Marchenko–Pastur law
  The Marchenko–Pastur law is a probability distribution that describes the asymptotic eigenvalue spectrum of large random covariance matrices in random matrix theory.
• F. None of above.
• G. Unsure - the case is ambiguous/there is not enough information to decide.