Triple

T18204624
Position Surface form Disambiguated ID Type / Status
Subject ViT E435871 entity
Predicate openSourceImplementation P7052 FINISHED
Object timm library NE NERFINISHED

How this triple was built (3 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: timm library | Statement: [ViT, openSourceImplementation, timm library]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: timm library
Context triple: [ViT, openSourceImplementation, timm library]
  • A. torchvision (ecosystem)
    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. TensorFlow Hub
    TensorFlow Hub is a library and online repository of reusable machine learning models and components designed to simplify sharing and deploying pretrained models in TensorFlow applications.
  • C. ResNeXt
    ResNeXt is a deep convolutional neural network architecture that extends ResNet by using grouped convolutions and a split-transform-merge strategy to improve accuracy and efficiency in image recognition tasks.
  • D. ViT
    ViT (Vision Transformer) is a deep learning model architecture that applies the transformer framework to image recognition tasks by treating images as sequences of patches.
  • E. Caffe Model Zoo
    Caffe Model Zoo is a public collection of pre-trained deep learning models shared by the Caffe community for tasks like image classification, detection, and segmentation.
  • 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: timm library
Target entity description: The timm library is a popular PyTorch-based collection of image models, layers, utilities, and pretrained weights widely used for state-of-the-art computer vision research and applications.
  • A. torchvision (ecosystem)
    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. TensorFlow Hub
    TensorFlow Hub is a library and online repository of reusable machine learning models and components designed to simplify sharing and deploying pretrained models in TensorFlow applications.
  • C. ResNeXt
    ResNeXt is a deep convolutional neural network architecture that extends ResNet by using grouped convolutions and a split-transform-merge strategy to improve accuracy and efficiency in image recognition tasks.
  • D. ViT
    ViT (Vision Transformer) is a deep learning model architecture that applies the transformer framework to image recognition tasks by treating images as sequences of patches.
  • E. Caffe Model Zoo
    Caffe Model Zoo is a public collection of pre-trained deep learning models shared by the Caffe community for tasks like image classification, detection, and segmentation.
  • F. None of above. chosen

Provenance (2 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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e222831081908f7d5500424e3acb completed April 19, 2026, 2:09 p.m.
Created at: April 10, 2026, 10:32 a.m.