Triple
T14375045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PicScout |
E356452
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | image recognition company |
C423
|
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: image recognition company Context triple: [PicScout, instanceOf, image recognition company]
-
A.
image recognition model
An image recognition model is a computational system that analyzes visual input to automatically identify, classify, and sometimes localize objects, patterns, or features within images.
-
B.
multimedia search company
A multimedia search company develops technology and services that enable users to efficiently find, organize, and retrieve diverse media content—such as images, videos, audio, and documents—across various platforms and data sources.
-
C.
company
chosen
A company is an organized entity, legally recognized or informally structured, that coordinates people and resources to produce goods or services for customers, typically in pursuit of profit or specific objectives.
-
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.
Data and AI company
A Data and AI company specializes in collecting, managing, and analyzing data to build intelligent systems and solutions that automate decisions, generate insights, and create predictive or generative capabilities for businesses.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
Created at: April 10, 2026, 1:16 a.m.