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: Deep Learning: A Revolutionary Approach to Artificial Intelligence | Statement: [Deep Learning: A Revolutionary Approach to Artificial Intelligence, hasTitle, Deep Learning: A Revolutionary Approach to Artificial Intelligence]

Target entity: Deep Learning: A Revolutionary Approach to Artificial Intelligence
Context triple: [Deep Learning: A Revolutionary Approach to Artificial Intelligence, hasTitle, Deep Learning: A Revolutionary Approach to Artificial Intelligence]

• A. Deep Learning: A Revolutionary Approach to Artificial Intelligence chosen
  "Deep Learning: A Revolutionary Approach to Artificial Intelligence" is a book by neuroscientist and AI researcher Terrence Sejnowski that explains the principles, history, and impact of deep learning for a broad audience.
• B. Deep Learning (book)
  Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
• C. ImageNet Classification with Deep Convolutional Neural Networks
  "ImageNet Classification with Deep Convolutional Neural Networks" is the landmark 2012 research paper that introduced the deep CNN model AlexNet, demonstrating a dramatic leap in image recognition performance on the ImageNet benchmark and catalyzing the modern deep learning revolution in computer vision.
• D. Cambrian intelligence: The early history of the new AI
  Cambrian Intelligence: The Early History of the New AI is a book by roboticist Rodney Brooks that outlines his influential behavior-based approach to artificial intelligence and robotics in contrast to traditional symbolic AI.
• E. “Learning representations by back-propagating errors”
  “Learning representations by back-propagating errors” is a landmark 1986 research paper that popularized the backpropagation algorithm for training multi-layer neural networks, helping to launch the modern field of deep learning.
• F. None of above.
• G. Unsure - the case is ambiguous/there is not enough information to decide.