Triple
T3845962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coca-Cola Refreshments |
E93569
|
entity |
| Predicate | brandManaged |
P42952
|
FINISHED |
| Object | Minute Maid |
E85133
|
NE 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: Minute Maid | Statement: [Coca-Cola Refreshments, brandManaged, Minute Maid]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minute Maid Context triple: [Coca-Cola Refreshments, brandManaged, Minute Maid]
-
A.
Minute Maid
chosen
Minute Maid is a well-known beverage brand specializing in fruit juices and juice drinks, owned by The Coca-Cola Company.
-
B.
Nestea
Nestea is a popular ready-to-drink and powdered iced tea beverage brand originally developed and marketed by Nestlé.
-
C.
Nuka-Cola
Nuka-Cola is a fictional, highly recognizable soft drink brand in the Fallout video game universe, symbolizing the series’ retro-futuristic, post-apocalyptic setting.
-
D.
P-Cola
P-Cola is a common shorthand nickname for the city of Pensacola in the Florida Panhandle.
-
E.
Gala Brand
Gala Brand is a fictional Special Branch officer and Bond girl who appears in Ian Fleming’s James Bond novel "Moonraker."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb77a488190be7fc2a1211f1f2d |
completed | March 9, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b504122cb08190ba97ce14e8d891fc |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:18 p.m.