Triple

T5305976
Position Surface form Disambiguated ID Type / Status
Subject Bausch + Lomb E120103 entity
Predicate brand P1500 FINISHED
Object Biotrue
Biotrue is a Bausch + Lomb eye care brand best known for its contact lens solutions and lubricating eye drops designed to mimic the eye’s natural biology.
 E120103 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: Biotrue | Statement: [Bausch + Lomb, brand, Biotrue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Biotrue
Context triple: [Bausch + Lomb, brand, Biotrue]
  • A. Bausch + Lomb
    Bausch + Lomb is a global eye health company best known for its contact lenses, lens care products, and ophthalmic pharmaceuticals.
  • B. Marico Eye
    Marico Eye is a clear natural spring in South Africa that forms the primary headwaters of the Marico River.
  • C. Biolon
    Biolon is a tributary stream that feeds into Lake Annecy in southeastern France.
  • D. Allergan
    Allergan is a global pharmaceutical company best known for developing branded drugs and medical aesthetics products, including Botox.
  • E. CeraVe
    CeraVe is a dermatologist-developed skincare brand known for its ceramide-rich, fragrance-free products designed to restore and protect the skin barrier.
  • 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: Biotrue
Triple: [Bausch + Lomb, brand, Biotrue]
Generated description
Biotrue is a Bausch + Lomb eye care brand best known for its contact lens solutions and lubricating eye drops designed to mimic the eye’s natural biology.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Biotrue
Target entity description: Biotrue is a Bausch + Lomb eye care brand best known for its contact lens solutions and lubricating eye drops designed to mimic the eye’s natural biology.
  • A. Bausch + Lomb chosen
    Bausch + Lomb is a global eye health company best known for its contact lenses, lens care products, and ophthalmic pharmaceuticals.
  • B. Marico Eye
    Marico Eye is a clear natural spring in South Africa that forms the primary headwaters of the Marico River.
  • C. Biolon
    Biolon is a tributary stream that feeds into Lake Annecy in southeastern France.
  • D. Allergan
    Allergan is a global pharmaceutical company best known for developing branded drugs and medical aesthetics products, including Botox.
  • E. CeraVe
    CeraVe is a dermatologist-developed skincare brand known for its ceramide-rich, fragrance-free products designed to restore and protect the skin barrier.
  • F. None of above.

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_69bd44704be88190acdb2ac481b0ff55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd851dd0d081909c0bf1423278ad8a completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf10f77b048190b8d3b39b900008d8 completed March 21, 2026, 9:43 p.m.
NEDg Description generation batch_69bf1186f1988190893e8d1af8623f6d completed March 21, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_69bf1226ddd08190a39799fd0db58694 completed March 21, 2026, 9:48 p.m.
Created at: March 20, 2026, 1:53 p.m.