Triple
T20878409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wonka brand |
E514080
|
entity |
| Predicate | ownedBy |
P347
|
FINISHED |
| Object | Ferrero Group |
—
|
NE NERFINISHED |
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: Ferrero Group | Statement: [Wonka brand, ownedBy, Ferrero Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ferrero Group Context triple: [Wonka brand, ownedBy, Ferrero Group]
-
A.
Ferrero
chosen
Ferrero is an Italian multinational confectionery and chocolate manufacturer best known for brands such as Nutella, Ferrero Rocher, Kinder, and Tic Tac.
-
B.
Nestlé
Nestlé is a Swiss multinational food and beverage conglomerate and one of the world’s largest consumer goods companies.
-
C.
Lindt & Sprüngli
Lindt & Sprüngli is a Swiss premium chocolate and confectionery manufacturer renowned worldwide for its high-quality chocolate bars, pralines, and seasonal specialties.
-
D.
Mondelez International
Mondelez International is a global snack and confectionery company known for brands like Oreo, Cadbury, and Toblerone.
-
E.
Danone
Danone is a multinational French food-products corporation best known for its dairy, plant-based, and bottled water brands.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c6775f108190a79cd5e8c31cecf6 |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 12:45 p.m.