Triple
T3520344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VGG |
E74406
|
entity |
| Predicate | developedBy |
P73
|
FINISHED |
| Object |
Visual Geometry Group
The Visual Geometry Group is a renowned computer vision research group at the University of Oxford known for pioneering deep convolutional neural network architectures such as VGGNet.
|
E366100
|
NE FINISHED |
How this triple was built (4 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: Visual Geometry Group | Statement: [VGG, developedBy, Visual Geometry Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Visual Geometry Group Context triple: [VGG, developedBy, Visual Geometry Group]
-
A.
Learning to See by Moving
"Learning to See by Moving" is a research work in computer vision that explores how visual understanding can emerge from an agent’s own movement and interaction with the environment, rather than from static images alone.
-
B.
Scene Completion Using Millions of Photographs
"Scene Completion Using Millions of Photographs" is a seminal computer vision and graphics paper that introduced a data-driven method for automatically filling in missing regions of images by searching a massive online photo collection for visually compatible patches.
-
C.
Data-Driven Hallucination of Different Views
"Data-Driven Hallucination of Different Views" is a computer vision research work by Alexei Efros that uses data-driven techniques to synthesize plausible novel viewpoints of a scene from a single or limited set of images.
-
D.
Visual Component Library
Visual Component Library is Delphi’s native GUI framework that provides a rich set of reusable visual and non-visual components for building Windows applications.
-
E.
Max Planck Institute for Intelligent Systems
The Max Planck Institute for Intelligent Systems is a leading German research institute focused on advancing the understanding and development of intelligent systems, including machine learning, robotics, and related fields.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Visual Geometry Group Triple: [VGG, developedBy, Visual Geometry Group]
Generated description
The Visual Geometry Group is a renowned computer vision research group at the University of Oxford known for pioneering deep convolutional neural network architectures such as VGGNet.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Visual Geometry Group Target entity description: The Visual Geometry Group is a renowned computer vision research group at the University of Oxford known for pioneering deep convolutional neural network architectures such as VGGNet.
-
A.
Learning to See by Moving
"Learning to See by Moving" is a research work in computer vision that explores how visual understanding can emerge from an agent’s own movement and interaction with the environment, rather than from static images alone.
-
B.
Scene Completion Using Millions of Photographs
"Scene Completion Using Millions of Photographs" is a seminal computer vision and graphics paper that introduced a data-driven method for automatically filling in missing regions of images by searching a massive online photo collection for visually compatible patches.
-
C.
Data-Driven Hallucination of Different Views
"Data-Driven Hallucination of Different Views" is a computer vision research work by Alexei Efros that uses data-driven techniques to synthesize plausible novel viewpoints of a scene from a single or limited set of images.
-
D.
Visual Component Library
Visual Component Library is Delphi’s native GUI framework that provides a rich set of reusable visual and non-visual components for building Windows applications.
-
E.
Max Planck Institute for Intelligent Systems
The Max Planck Institute for Intelligent Systems is a leading German research institute focused on advancing the understanding and development of intelligent systems, including machine learning, robotics, and related fields.
- F. None of above. chosen
Provenance (5 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc4af70c8190a7471f28e1efd7fd |
completed | March 8, 2026, 6:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e848d1c8190b100cb2e1218afbb |
completed | March 13, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_69b37f07ab70819089fdb7083b81b992 |
completed | March 13, 2026, 3:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b38078bc288190b69d73a64acce8ca |
completed | March 13, 2026, 3:11 a.m. |
Created at: March 8, 2026, 3:19 p.m.