Triple

T5933502
Position Surface form Disambiguated ID Type / Status
Subject Danone E131990 entity
Predicate foundedAs P364 FINISHED
Object Danone (Barcelona yogurt company) 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 (Barcelona yogurt company) | Statement: [Danone, foundedAs, Danone (Barcelona yogurt company)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danone (Barcelona yogurt company)
Context triple: [Danone, foundedAs, Danone (Barcelona yogurt company)]
  • A. Danone chosen
    Danone is a multinational French food-products corporation best known for its dairy, plant-based, and bottled water brands.
  • B. Nestlé
    Nestlé is a Swiss multinational food and beverage conglomerate and one of the world’s largest consumer goods companies.
  • C. Knorr
    Knorr is a global food brand known for its soups, seasonings, bouillon, and ready-made meal products.
  • D. Saputo Inc.
    Saputo Inc. is a major Canadian dairy company that produces and distributes a wide range of cheese and other dairy products internationally.
  • E. Yakult Honsha
    Yakult Honsha is a Japanese company best known for producing Yakult probiotic drinks and other dairy-based beverages.
  • 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_69c0085c55dc8190aa90e242c956e2fa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0389f6fc881909527b928838ffcdd completed March 22, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c064d2a4819096085668182cfde1 completed March 23, 2026, 4:24 a.m.
Created at: March 22, 2026, 4 p.m.