Triple

T12451691
Position Surface form Disambiguated ID Type / Status
Subject ULVR E297546 entity
Predicate associatedWithBrandPortfolio P99659 FINISHED
Object Becel
Becel is a well-known margarine and plant-based spread brand marketed for heart health and lower cholesterol.
 E985209 NE FINISHED

How this triple was built (4 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: Becel | Statement: [ULVR, associatedWithBrandPortfolio, Becel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Becel
Context triple: [ULVR, associatedWithBrandPortfolio, Becel]
  • A. Knorr
    Knorr is a global food brand known for its soups, seasonings, bouillon, and ready-made meal products.
  • B. Tnuva
    Tnuva is Israel’s largest food manufacturer and leading dairy company, known for its wide range of milk and dairy products.
  • C. Dr. Oetker
    Dr. Oetker is a German multinational food company best known for its baking products, desserts, frozen pizzas, and other convenience foods.
  • D. Bunge
    Bunge is the unicameral legislative body and main law-making institution of the United Republic of Tanzania.
  • E. Bunge
    Bunge is a surname most notably associated with Nikolai Bunge, a prominent 19th-century Russian economist and statesman.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Becel
Triple: [ULVR, associatedWithBrandPortfolio, Becel]
Generated description
Becel is a well-known margarine and plant-based spread brand marketed for heart health and lower cholesterol.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Becel
Target entity description: Becel is a well-known margarine and plant-based spread brand marketed for heart health and lower cholesterol.
  • A. Knorr
    Knorr is a global food brand known for its soups, seasonings, bouillon, and ready-made meal products.
  • B. Tnuva
    Tnuva is Israel’s largest food manufacturer and leading dairy company, known for its wide range of milk and dairy products.
  • C. Dr. Oetker
    Dr. Oetker is a German multinational food company best known for its baking products, desserts, frozen pizzas, and other convenience foods.
  • D. Bunge
    Bunge is the unicameral legislative body and main law-making institution of the United Republic of Tanzania.
  • E. Bunge
    Bunge is a surname most notably associated with Nikolai Bunge, a prominent 19th-century Russian economist and statesman.
  • F. None of above. chosen

Provenance (5 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541ace208190a5149b6f18fa196d completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f16e87c8190b7e9f61561ae865a completed May 2, 2026, 6:14 p.m.
NEDg Description generation batch_69f6412345ac8190826f4fecb8055fb5 completed May 2, 2026, 6:23 p.m.
NED2 Entity disambiguation (via description) batch_69f64231606481909b8dd9d878670a6c completed May 2, 2026, 6:28 p.m.
Created at: April 8, 2026, 9:56 p.m.