Triple
T22919599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RC Cola |
E568822
|
entity |
| Predicate | isSoftDrinkBrand |
P150258
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [RC Cola, isSoftDrinkBrand, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSoftDrinkBrand Context triple: [RC Cola, isSoftDrinkBrand, true]
-
A.
isSoftDrink
Indicates that something is classified as a soft drink, typically a non-alcoholic, carbonated or sweetened beverage.
-
B.
isSoftDrinkVariantOf
Indicates that one soft drink is a specific version, flavor, or formulation derived from or based on another soft drink.
-
C.
beerBrand
Indicates that one entity is a brand designation for a particular type or product of beer associated with the other entity.
-
D.
canBeCarbonated
Indicates that the subject is capable of being made carbonated, typically by dissolving carbon dioxide under pressure.
-
E.
hasCarbonatedWater
Indicates that an entity contains or is associated with carbonated (fizzy) water as a component or ingredient.
- F. None of above. chosen
Provenance (4 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180d316188190901d9356c07110e3 |
completed | April 29, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:42 p.m.