Triple

T11115645
Position Surface form Disambiguated ID Type / Status
Subject Nicorette E262877 entity
Predicate ownedBy P347 FINISHED
Object Kenvue E50225 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: Kenvue | Statement: [Nicorette, ownedBy, Kenvue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenvue
Context triple: [Nicorette, ownedBy, Kenvue]
  • A. Kenvue chosen
    Kenvue is a consumer health company that owns well-known over-the-counter medicine and personal care brands formerly housed within Johnson & Johnson.
  • B. Baxter International
    Baxter International is a global healthcare company specializing in medical devices, pharmaceuticals, and biotechnology products, particularly in areas such as renal care, critical care, and hospital products.
  • C. Johnson & Johnson
    Johnson & Johnson is a multinational healthcare conglomerate best known for its pharmaceuticals, medical devices, and consumer health products.
  • D. Danaher Corporation
    Danaher Corporation is a diversified global science and technology conglomerate known for its portfolio of life sciences, diagnostics, and industrial solutions businesses.
  • E. Lonza
    Lonza is a global Swiss-based life sciences company specializing in pharmaceutical, biotech, and nutrition products and services, particularly in contract development and manufacturing.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79aa7254c8190abce35696ad2be03 completed April 9, 2026, 12:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441cb16bc81908b5321506f655e38 completed April 19, 2026, 2:45 a.m.
Created at: April 8, 2026, 9:27 p.m.