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: Mastering the game of Go with deep neural networks and tree search | Statement: [Ioannis Antonoglou, coAuthorOf, Mastering the game of Go with deep neural networks and tree search]

Target entity: Mastering the game of Go with deep neural networks and tree search
Context triple: [Ioannis Antonoglou, coAuthorOf, Mastering the game of Go with deep neural networks and tree search]

• A. AlphaGo Zero chosen
  AlphaGo Zero is DeepMind's advanced artificial intelligence program that learned to play the board game Go at superhuman level entirely through self-play without human data.
• B. Monte Carlo tree search
  Monte Carlo tree search is a heuristic search algorithm that uses random sampling of game states to build and explore a search tree, enabling strong decision-making in complex domains like Go and other board games.
• C. MuZero
  MuZero is a DeepMind reinforcement learning algorithm that learns to plan and master complex games like Go, chess, and Atari without being given the rules in advance.
• D. AlphaGo
  AlphaGo is an artificial intelligence program developed by DeepMind that became famous for defeating world champion Go players using deep neural networks and reinforcement learning.
• E. Atari deep Q-network
  The Atari deep Q-network is a pioneering deep reinforcement learning system that learned to play a wide range of Atari 2600 video games directly from raw pixels at human-level or better performance.
• F. None of above.
• G. Unsure - the case is ambiguous/there is not enough information to decide.