Triple
T18016067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VOCSegmentation |
E431001
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | torchvision.datasets.VisionDataset subclass |
C38260
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: torchvision.datasets.VisionDataset subclass Context triple: [VOCSegmentation, instanceOf, torchvision.datasets.VisionDataset subclass]
-
A.
PyTorch ecosystem project
A PyTorch ecosystem project is a library, tool, or framework that extends or integrates with PyTorch to support tasks such as model development, training, deployment, or domain-specific applications.
-
B.
open-source dataset
chosen
An open-source dataset is a collection of data made freely available for anyone to access, use, modify, and share, typically under a permissive license.
-
C.
torch
A torch is a portable light source, traditionally a stick with a combustible material at one end and in modern usage often a handheld electric device, used to illuminate dark areas.
-
D.
computer vision algorithm
A computer vision algorithm is a computational method that processes and interprets visual data from images or videos to automatically extract meaningful information or perform tasks such as detection, recognition, and segmentation.
-
E.
NSObject subclass
An NSObject subclass is a custom class in Objective-C (or Swift via bridging) that inherits from the root NSObject class to gain fundamental runtime, memory management, and messaging behavior in the Cocoa/Cocoa Touch frameworks.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
Created at: April 10, 2026, 10:24 a.m.