Triple
T15361355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiming He |
E367295
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Faster R-CNN (paper) |
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 (paper) Context triple: [Kaiming He, notableWork, Faster R-CNN (paper)]
-
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.
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_69d85a1483788190ad93c2748e8af34b |
elicitation | completed |
| NER | batch_69e03e4607408190ab281a7f7a8012d3 |
ner | completed |
| NED1 | batch_69ff219863b48190a68e73c85e27472c |
ned_source_triple | completed |
Created at: April 10, 2026, 3:18 a.m.