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: autocorrelation theorem | Statement: [Wiener–Khinchin theorem, alsoKnownAs, autocorrelation theorem]

Target entity: autocorrelation theorem
Context triple: [Wiener–Khinchin theorem, alsoKnownAs, autocorrelation theorem]

• A. Wiener–Khinchin theorem chosen
  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.
• B. convolution theorem
  The convolution theorem is a fundamental result in Fourier analysis stating that convolution in one domain corresponds to pointwise multiplication in the Fourier-transformed domain (and vice versa), greatly simplifying the analysis of linear systems.
• C. Fourier inversion theorem
  The Fourier inversion theorem is a fundamental result in harmonic analysis that guarantees, under suitable conditions, that a function can be exactly reconstructed from its Fourier transform.
• D. Wiener filter
  The Wiener filter is a signal processing technique that optimally estimates a desired signal from noisy observations by minimizing the mean square error, based on statistical properties of signal and noise.
• E. Nyquist theorem
  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.
• F. None of above.
• G. Unsure - the case is ambiguous/there is not enough information to decide.