Triple

T3428416
Position Surface form Disambiguated ID Type / Status
Subject LVMH E72279 entity
Predicate ownsBrand P1500 FINISHED
Object Fenty Beauty E85465 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: Fenty Beauty | Statement: [LVMH, ownsBrand, Fenty Beauty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fenty Beauty
Context triple: [LVMH, ownsBrand, Fenty Beauty]
  • A. Fenty chosen
    Fenty is the surname of global music and fashion icon Rihanna, which she also uses as the brand name for her beauty and fashion ventures.
  • B. Maybelline New York
    Maybelline New York is a major American cosmetics and beauty brand known worldwide for its mass-market makeup products.
  • C. NYX Professional Makeup
    NYX Professional Makeup is a popular, affordable cosmetics brand known for its wide range of highly pigmented, trend-driven makeup products favored by both professionals and everyday consumers.
  • D. Kylie Cosmetics
    Kylie Cosmetics is a makeup and beauty brand founded by Kylie Jenner, known for its trend-setting lip kits and social media–driven marketing.
  • E. Essie
    Essie is a popular nail polish and nail care brand known for its wide range of fashion-forward colors and salon-quality formulas.
  • 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_69ad85ae14308190bcbc25cfa0246c0b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb983f4608190abcc27aa7b926deb completed March 8, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69b35478448481908e1c0f717d99f992 completed March 13, 2026, 12:04 a.m.
Created at: March 8, 2026, 3:15 p.m.