Triple
T17076768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | non-alcoholic beverages industry |
E414368
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | part of food and beverage industry |
C38774
|
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: part of food and beverage industry Context triple: [non-alcoholic beverages industry, instanceOf, part of food and beverage industry]
-
A.
food and beverage location
A food and beverage location is a place where customers can purchase and consume prepared food and drinks, such as restaurants, cafés, bars, or food courts.
-
B.
foodservice industry event
A foodservice industry event is a planned gathering where professionals and stakeholders in the food and beverage sector meet to network, showcase products, share knowledge, and explore business opportunities.
-
C.
airline catering company
An airline catering company is a specialized service provider that prepares, packages, and delivers meals, beverages, and related onboard provisions to airlines for in-flight service.
-
D.
multinational beverage and brewing company
A multinational beverage and brewing company is a global enterprise that produces, markets, and distributes a wide range of alcoholic and non-alcoholic drinks across multiple countries and regions.
-
E.
food ingredient manufacturer
A food ingredient manufacturer is a company that produces and supplies raw or processed components—such as flavors, additives, and functional ingredients—to food and beverage producers for use in their finished products.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
Created at: April 10, 2026, 5:34 a.m.