Triple
T26562441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Bull Coconut Edition |
E666286
|
entity |
| Predicate | energyDrinkCategory |
P70752
|
FINISHED |
| Object | functional beverage |
—
|
LITERAL FINISHED |
How this triple was built (2 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: functional beverage | Statement: [Red Bull Coconut Edition, energyDrinkCategory, functional beverage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: energyDrinkCategory Context triple: [Red Bull Coconut Edition, energyDrinkCategory, functional beverage]
-
A.
beverageSubcategory
Indicates a more specific classification within a broader beverage category, defining the subtype or subcategory of a drink.
-
B.
drinks
Indicates that one entity consumes a liquid substance, typically by ingesting it through the mouth.
-
C.
beverageBase
Indicates that one entity serves as the primary liquid or foundational ingredient used to make a beverage involving the other entity.
-
D.
hasBeverageCategory
chosen
Indicates that an entity is associated with or classified under a particular beverage category.
-
E.
typicalCaffeineSource
Indicates that one entity is a common or characteristic source from which the other entity typically obtains caffeine.
- F. None of above.
Provenance (3 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_69ee9cf7e94481909f0d556b36e43572 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c663be481908f233d25d28713a4 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 1:53 a.m.