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: Going Deeper with Convolutions | Statement: [Christian Szegedy, notableWork, Going Deeper with Convolutions]

Target entity: Going Deeper with Convolutions
Context triple: [Christian Szegedy, notableWork, Going Deeper with Convolutions]

• A. Inception architecture chosen
  The Inception architecture is a deep convolutional neural network design that introduced parallel multi-scale processing modules to achieve state-of-the-art image recognition performance with improved computational efficiency.
• 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. ResNet
  ResNet is a deep convolutional neural network architecture known for its use of residual connections to enable very deep models and achieve state-of-the-art performance in image recognition tasks.
• D. Deep belief networks
  Deep belief networks are a class of deep generative neural network models composed of stacked layers of latent variables, typically built from restricted Boltzmann machines, used for unsupervised feature learning and representation.
• 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.