Triple
T4325978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | torchvision |
E96634
|
entity |
| Predicate | hasSubmodule |
P25619
|
FINISHED |
| Object | torchvision.transforms |
E96634
|
NE FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
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).
Input
Phrase: torchvision.transforms | Statement: [torchvision, hasSubmodule, torchvision.transforms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: torchvision.transforms Context triple: [torchvision, hasSubmodule, torchvision.transforms]
-
A.
torchvision (ecosystem)
chosen
torchvision is a PyTorch-based computer vision library providing datasets, model architectures, and image transformations commonly used for training and evaluating deep learning models.
-
B.
PyTorch
PyTorch is an open-source deep learning framework widely used for building and training neural networks, known for its dynamic computation graph and strong support for research and production in Python.
-
C.
NVIDIA Image Scaling
NVIDIA Image Scaling is a driver-based spatial upscaling and sharpening feature from NVIDIA that boosts game performance and clarity by rendering at lower resolutions and scaling images in real time.
-
D.
CycleGAN
CycleGAN is a type of generative adversarial network designed for unpaired image-to-image translation, enabling conversion between visual domains without requiring matched training examples.
-
E.
CIFAR
CIFAR (the Canadian Institute for Advanced Research) is a Canadian global research organization that supports long-term, collaborative, interdisciplinary research, including major initiatives in artificial intelligence.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3563eab24819088add9180af2ce3c |
completed | March 13, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d09861a4819086a88bb42a8ea2e4 |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:13 p.m.