Triple
T21401341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vitaflo |
E527919
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Nestlé 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: Nestlé Group | Statement: [Vitaflo, partOf, Nestlé Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nestlé Group Context triple: [Vitaflo, partOf, Nestlé Group]
-
A.
Nestlé
chosen
Nestlé is a Swiss multinational food and beverage conglomerate and one of the world’s largest consumer goods companies.
-
B.
Danone
Danone is a multinational French food-products corporation best known for its dairy, plant-based, and bottled water brands.
-
C.
Kraft Group
Kraft Group is a privately held American conglomerate best known for its ownership of major New England sports franchises and extensive interests in paper, packaging, real estate, and private equity.
-
D.
Mondelez International
Mondelez International is a global snack and confectionery company known for brands like Oreo, Cadbury, and Toblerone.
-
E.
Unilever
Unilever is a multinational consumer goods company known for its wide range of food, personal care, and household products sold globally.
- 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_69e0b520ee3c8190abddbee7e37e834c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b16f7c5081909475eb5bb6177955 |
completed | April 22, 2026, 11:30 a.m. |
Created at: April 16, 2026, 5:15 p.m.