Triple
T5432386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eberhard Nestle |
E121526
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nestle |
E27582
|
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: Nestle | Statement: [Eberhard Nestle, familyName, Nestle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nestle Context triple: [Eberhard Nestle, familyName, Nestle]
-
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 Foods
Kraft Foods is a major American food and beverage company known for producing a wide range of packaged grocery products and iconic brands such as Kraft cheese and Oscar Mayer.
-
D.
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.
-
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 (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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8840ade481909dae2eecc77d73b8 |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3ac985e48190ba9610e0563c73ab |
completed | March 22, 2026, 12:41 a.m. |
Created at: March 20, 2026, 2:06 p.m.