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: Faster R-CNN | Statement: [Mask R-CNN, extends, Faster R-CNN]

Target entity: Faster R-CNN
Context triple: [Mask R-CNN, extends, Faster R-CNN]

• A. R-CNN
  R-CNN is a pioneering deep learning framework for object detection that combines region proposals with convolutional neural networks to accurately localize and classify objects in images.
• B. FasterRCNN chosen
  FasterRCNN is a popular two-stage object detection architecture that first proposes candidate regions and then classifies and refines bounding boxes, widely used in computer vision tasks.
• C. RCNN
  RCNN is the ICAO airport code assigned to Tainan Airport in Tainan, Taiwan.
• D. Feature Pyramid Networks based detectors
  Feature Pyramid Networks based detectors are a family of object detection models that enhance multi-scale feature representation by building top-down feature hierarchies with lateral connections, improving accuracy for objects of varying sizes.
• E. Region Proposal Network
  A Region Proposal Network is a deep learning module that efficiently generates candidate object bounding boxes directly from feature maps for use in modern object detection systems.
• F. None of above.
• G. Unsure - the case is ambiguous/there is not enough information to decide.