Triple
T18016068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VOCSegmentation |
E431001
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | semantic segmentation dataset class |
C40300
|
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: semantic segmentation dataset class Context triple: [VOCSegmentation, instanceOf, semantic segmentation dataset class]
-
A.
points classification
Points classification is a conceptual class that categorizes entities based on accumulated points or scores according to predefined criteria or performance metrics.
-
B.
classification board
A classification board is an authoritative body or panel that evaluates and assigns categories, ratings, or classifications to items such as media, products, or information based on defined criteria and standards.
-
C.
urban design recognition
Urban design recognition is the process of identifying, interpreting, and classifying the spatial, visual, and functional patterns of built environments within cities.
-
D.
public land classification
Public land classification is the systematic categorization of government-owned lands based on their designated uses, protections, and management objectives, such as conservation, recreation, resource extraction, or development.
-
E.
social classification
Social classification is the systematic process of categorizing individuals or groups within a society based on attributes such as socioeconomic status, ethnicity, gender, occupation, or education, which shapes their access to resources, power, and opportunities.
- F. None of above. chosen
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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
Created at: April 10, 2026, 10:24 a.m.