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: Nyquist–Shannon sampling theorem | Statement: [Nyquist theorem, alsoKnownAs, Nyquist–Shannon sampling theorem]

Target entity: Nyquist–Shannon sampling theorem
Context triple: [Nyquist theorem, alsoKnownAs, Nyquist–Shannon sampling theorem]

• A. Nyquist theorem chosen
  The Nyquist theorem is a fundamental principle in signal processing that states a continuous signal can be perfectly reconstructed from its samples if it is sampled at more than twice its highest frequency component.
• B. Wiener–Khinchin theorem
  The Wiener–Khinchin theorem is a fundamental result in signal processing and probability theory that relates a wide-sense stationary random process’s autocorrelation function to its power spectral density via the Fourier transform.
• C. Parseval's theorem
  Parseval's theorem is a fundamental result in Fourier analysis that equates the total energy of a function in the time (or spatial) domain with the total energy of its representation in the frequency domain.
• D. Slepian–Wolf coding theorem
  The Slepian–Wolf coding theorem is a fundamental result in information theory that characterizes the limits of lossless data compression for correlated sources encoded separately but decoded jointly.
• E. Cooley–Tukey Fast Fourier Transform algorithm
  The Cooley–Tukey Fast Fourier Transform algorithm is a widely used, efficient method for computing the discrete Fourier transform that revolutionized digital signal processing and numerical analysis.
• F. None of above.
• G. Unsure - the case is ambiguous/there is not enough information to decide.