Triple
T10550698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swire Coca-Cola |
E248938
|
entity |
| Predicate | brandPortfolioIncludes |
P18121
|
FINISHED |
| Object | Schweppes |
E90826
|
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: Schweppes | Statement: [Swire Coca-Cola, brandPortfolioIncludes, Schweppes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schweppes Context triple: [Swire Coca-Cola, brandPortfolioIncludes, Schweppes]
-
A.
Schweppes
chosen
Schweppes is a historic beverage brand best known for its carbonated soft drinks and tonic waters, now owned and marketed in many regions by The Coca-Cola Company.
-
B.
Vittel
Vittel is a French spa town renowned for its mineral water springs and bottled water brand, located in northeastern France.
-
C.
Innocent Drinks
Innocent Drinks is a UK-based beverage company best known for its fruit smoothies, juices, and health-focused drinks made with natural ingredients.
-
D.
Perrier
Perrier is a French brand of naturally carbonated mineral water known for its distinctive green bottles and strong sparkling taste.
-
E.
Coca-Cola Refreshments
Coca-Cola Refreshments is a major bottling and distribution subsidiary responsible for producing and delivering Coca-Cola beverages to retailers and consumers.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d526d4c4048190a104d6e088f565b3 |
completed | April 7, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d934639b3481908204db41101132c3 |
completed | April 10, 2026, 5:33 p.m. |
Created at: April 6, 2026, 12:34 p.m.