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: Laplace smoothing | Statement: [Naive Bayes classifier, oftenUses, Laplace smoothing]

Target entity: Laplace smoothing
Context triple: [Naive Bayes classifier, oftenUses, Laplace smoothing]

• A. Laplace's rule of succession (as a special case) chosen
  Laplace's rule of succession is a classical Bayesian rule for estimating the probability of an event based on observed successes and failures, assigning a nonzero prior probability to unobserved outcomes.
• B. Pitman–Yor process models
  Pitman–Yor process models are Bayesian nonparametric models that generalize Dirichlet process models by allowing power-law behavior and heavier-tailed distributions over clusters.
• C. Bayesian text modeling
  Bayesian text modeling is a probabilistic approach to analyzing and generating text that uses Bayesian inference to estimate latent structures such as topics, word distributions, and document representations.
• D. Dirichlet distribution
  The Dirichlet distribution is a family of continuous multivariate probability distributions commonly used as a prior over categorical or multinomial parameters in Bayesian statistics.
• E. Bayes
  Bayes is a surname most famously associated with Thomas Bayes, the 18th-century statistician and minister whose work led to the development of Bayesian probability theory.
• F. None of above.
• G. Unsure - the case is ambiguous/there is not enough information to decide.