Triple
T232779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
E4443
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | machine learning conference |
C140
|
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: machine learning conference Context triple: [IEEE Computer Society Conference on Computer Vision and Pattern Recognition, instanceOf, machine learning conference]
-
A.
academic conference
chosen
An academic conference is a formal gathering of scholars, researchers, and professionals who present, discuss, and critique original research and developments within a specific field or interdisciplinary area.
-
B.
learned society
A learned society is an organization that exists to promote an academic discipline or group of related disciplines through research, communication, and professional collaboration among scholars and practitioners.
-
C.
diplomatic conference
A diplomatic conference is a formal gathering of representatives from different states or international organizations convened to negotiate agreements, resolve disputes, or discuss issues of mutual concern.
-
D.
research network
A research network is a structured system of interconnected researchers, institutions, and resources that collaboratively generate, share, and advance knowledge within and across disciplines.
-
E.
research consortium
A research consortium is a collaborative alliance of multiple organizations or institutions that pool resources, expertise, and infrastructure to conduct joint research toward shared scientific or technological goals.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.