Triple

T11658181
Position Surface form Disambiguated ID Type / Status
Subject ZEISS E277060 entity
Predicate brand P1500 FINISHED
Object ZEISS Vision Care E277060 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: ZEISS Vision Care | Statement: [ZEISS, brand, ZEISS Vision Care]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ZEISS Vision Care
Context triple: [ZEISS, brand, ZEISS Vision Care]
  • A. Bausch + Lomb
    Bausch + Lomb is a global eye health company best known for its contact lenses, lens care products, and ophthalmic pharmaceuticals.
  • B. Alcon
    Alcon is a global eye care company specializing in ophthalmic pharmaceuticals, surgical equipment, and vision care products.
  • C. ZEISS chosen
    ZEISS is a renowned German optics company best known for its high-quality lenses and imaging technologies used in cameras, microscopes, and industrial systems.
  • D. Allergan
    Allergan is a global pharmaceutical company best known for developing branded drugs and medical aesthetics products, including Botox.
  • E. Specsavers
    Specsavers is a British optical retail chain best known for providing affordable eye care and eyewear through its widespread network of high-street opticians.
  • 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a3d0331481909682b2e504e4c9a0 completed April 10, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee882148a08190a1a8c16d8cb7e48a completed April 26, 2026, 9:48 p.m.
Created at: April 8, 2026, 9:39 p.m.