Triple

T13867243
Position Surface form Disambiguated ID Type / Status
Subject Georgia May Jagger E333355 entity
Predicate notableWork P4 FINISHED
Object Rimmel London campaigns E884160 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: Rimmel London campaigns | Statement: [Georgia May Jagger, notableWork, Rimmel London campaigns]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rimmel London campaigns
Context triple: [Georgia May Jagger, notableWork, Rimmel London campaigns]
  • A. Rimmel chosen
    Rimmel is a British cosmetics brand best known for its affordable makeup products and the slogan "Get the London Look."
  • B. MAC Cosmetics
    MAC Cosmetics is a globally recognized professional makeup brand known for its wide range of high-quality cosmetics, trend-setting collaborations, and strong presence in the fashion and beauty industries.
  • C. Maybelline New York
    Maybelline New York is a major American cosmetics and beauty brand known worldwide for its mass-market makeup products.
  • 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. Too Faced
    Too Faced is a popular cosmetics brand known for its playful, feminine packaging and trend-driven makeup products.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c419d481909230e8879b6dab5c completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c1039128819086cfe9f966b9f142 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.