Triple

T15532289

Position	Surface form	Disambiguated ID	Type / Status
Subject	Shaoqing Ren	`E370248`	entity
Predicate	notableWork	`P4`	FINISHED
Object	Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks	`E431008`	NE FINISHED

Disambiguation candidates (1 decision)

The exact options the model was shown at each disambiguation step, with the option it chose highlighted — the evidence behind this triple's disambiguated ids.

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07

Target entity: Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Context triple: [Shaoqing Ren, notableWork, Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks]

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. RCNN
RCNN is the ICAO airport code assigned to Tainan Airport in Tainan, Taiwan.
C. 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.
D. RetinaNet
RetinaNet is a deep learning–based one-stage object detection model known for its focal loss function, which effectively addresses class imbalance to achieve high accuracy and speed.
E. MaskRCNN
MaskRCNN is a deep learning model architecture for instance segmentation that extends Faster R-CNN by adding a branch to predict segmentation masks for individual objects in an image.
F. None of above.
G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

Stage	Batch ID	Job type	Status
creating	`batch_69d85cc521a08190921fb50319dddc34`	elicitation	completed
NER	`batch_69e0414877d88190804ee76566004e13`	ner	completed
NED1	`batch_69ff56bdbca08190b5eb541c5eb4bb09`	ned_source_triple	completed

Created at: April 10, 2026, 4:06 a.m.