Triple
T13166421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evian |
E312860
|
entity |
| Predicate | parentCompany |
P254
|
FINISHED |
| Object | Danone |
E131990
|
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: Danone | Statement: [Evian, parentCompany, Danone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danone Context triple: [Evian, parentCompany, Danone]
-
A.
Danone
chosen
Danone is a multinational French food-products corporation best known for its dairy, plant-based, and bottled water brands.
-
B.
FrieslandCampina
FrieslandCampina is a large Dutch multinational dairy cooperative that produces and markets a wide range of dairy products worldwide.
-
C.
Nestlé
Nestlé is a Swiss multinational food and beverage conglomerate and one of the world’s largest consumer goods companies.
-
D.
National Dairy Products Corporation
National Dairy Products Corporation was a major American dairy and food processing company that later became known as Kraft Foods, one of the world’s largest food and beverage conglomerates.
-
E.
Tnuva
Tnuva is Israel’s largest food manufacturer and leading dairy company, known for its wide range of milk and dairy products.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c2c317881908cc715c97d915f77 |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5e22458819097dc8d6708df5284 |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 9:13 p.m.