Triple

T18016596
Position Surface form Disambiguated ID Type / Status
Subject KeypointRCNN E431011 entity
Predicate library P10267 FINISHED
Object torchvision NE NERFINISHED

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 | Statement: [KeypointRCNN, library, torchvision]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: torchvision
Context triple: [KeypointRCNN, library, torchvision]
  • 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. ChainerCV
    ChainerCV is a computer vision toolkit built on top of the Chainer deep learning framework, providing ready-to-use models and utilities for tasks like object detection and semantic segmentation.
  • D. Detectron
    Detectron is Facebook AI Research’s open-source computer vision framework that provides state-of-the-art implementations of object detection and segmentation models such as Mask R-CNN.
  • 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.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b9be5d0c819097e006f32d98753a completed April 19, 2026, 11:17 a.m.
Created at: April 10, 2026, 10:24 a.m.