COCO
E431000
COCO is a large-scale, richly annotated image dataset widely used in computer vision research for tasks like object detection, segmentation, and captioning.
All labels observed (1)
| Label | Occurrences |
|---|---|
| COCO canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4325990 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: COCO Context triple: [torchvision, dataset, COCO]
-
A.
Mamá Coco
Mamá Coco is the elderly, soft-spoken great-grandmother whose memories and family ties are central to the emotional core of Pixar’s animated film "Coco."
-
B.
Coco
Coco is the debut studio album by American singer-songwriter Colbie Caillat, featuring her breakout hit "Bubbly" and a laid-back acoustic pop sound.
-
C.
Coco
Coco is a 2017 Pixar animated film that follows a young Mexican boy’s journey through the Land of the Dead as he uncovers his family’s history and celebrates Día de los Muertos.
-
D.
Coco (Broadway musical)
Coco is a 1969 Broadway musical about the life of fashion designer Coco Chanel, featuring a score by André Previn and a book by Alan Jay Lerner.
-
E.
Kokovoko
Kokovoko is the fictional, remote South Pacific island homeland of Queequeg in Herman Melville’s novel "Moby-Dick."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: COCO Target entity description: COCO is a large-scale, richly annotated image dataset widely used in computer vision research for tasks like object detection, segmentation, and captioning.
-
A.
Mamá Coco
Mamá Coco is the elderly, soft-spoken great-grandmother whose memories and family ties are central to the emotional core of Pixar’s animated film "Coco."
-
B.
Coco
Coco is the debut studio album by American singer-songwriter Colbie Caillat, featuring her breakout hit "Bubbly" and a laid-back acoustic pop sound.
-
C.
Coco
Coco is a 2017 Pixar animated film that follows a young Mexican boy’s journey through the Land of the Dead as he uncovers his family’s history and celebrates Día de los Muertos.
-
D.
Coco (Broadway musical)
Coco is a 1969 Broadway musical about the life of fashion designer Coco Chanel, featuring a score by André Previn and a book by Alan Jay Lerner.
-
E.
Kokovoko
Kokovoko is the fictional, remote South Pacific island homeland of Queequeg in Herman Melville’s novel "Moby-Dick."
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
benchmark dataset
ⓘ
computer vision dataset ⓘ image dataset ⓘ |
| acronymFor | Common Objects in Context NERFINISHED ⓘ |
| associatedWith |
COCO captioning challenge
NERFINISHED
ⓘ
COCO detection challenge NERFINISHED ⓘ COCO segmentation challenge NERFINISHED ⓘ |
| contains | color images ⓘ |
| domain | computer vision ⓘ |
| evaluationMetric |
AP at multiple IoU thresholds
ⓘ
BLEU for captions ⓘ CIDEr for captions ⓘ SPICE for captions ⓘ mean Average Precision ⓘ |
| focusesOn |
common objects
ⓘ
everyday scenes ⓘ |
| fullName | Common Objects in Context NERFINISHED ⓘ |
| hasAnnotationType |
image-level captions
ⓘ
keypoints ⓘ object bounding boxes ⓘ segmentation masks ⓘ stuff segmentation ⓘ |
| hasProperty |
complex everyday scenes
ⓘ
contextual information ⓘ multiple objects per image ⓘ richly annotated ⓘ |
| hasSubset |
test set
ⓘ
training set ⓘ validation set ⓘ |
| license | permissive research license ⓘ |
| maintainedBy | computer vision research community ⓘ |
| relatedTo |
ImageNet
NERFINISHED
ⓘ
PASCAL VOC NERFINISHED ⓘ |
| scale | large-scale ⓘ |
| usedAs |
competition benchmark
ⓘ
standard benchmark ⓘ |
| usedFor |
image captioning
ⓘ
instance segmentation ⓘ keypoint detection ⓘ object detection ⓘ object recognition in context ⓘ panoptic segmentation ⓘ semantic segmentation ⓘ |
| usedIn |
academic research
ⓘ
deep learning model training ⓘ industrial research ⓘ machine learning model evaluation ⓘ |
| website | https://cocodataset.org/ ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: COCO Description of subject: COCO is a large-scale, richly annotated image dataset widely used in computer vision research for tasks like object detection, segmentation, and captioning.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
torchvision