Triple

T20071660
Position Surface form Disambiguated ID Type / Status
Subject Gigi Hadid E499752 entity
Predicate hasModeledFor P17880 FINISHED
Object Maybelline NE NERFINISHED

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: Maybelline | Statement: [Gigi Hadid, hasModeledFor, Maybelline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maybelline
Context triple: [Gigi Hadid, hasModeledFor, Maybelline]
  • A. Maybelline New York chosen
    Maybelline New York is a major American cosmetics and beauty brand known worldwide for its mass-market makeup products.
  • B. Rimmel
    Rimmel is a British cosmetics brand best known for its affordable makeup products and the slogan "Get the London Look."
  • C. 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.
  • D. Revlon
    Revlon is a major American cosmetics, skincare, fragrance, and personal care company known for its mass-market beauty products and global brand presence.
  • E. Benefit Cosmetics
    Benefit Cosmetics is a San Francisco–born beauty brand known for its playful packaging and bestselling brow and complexion products, and is part of the luxury group LVMH.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66438633481908710907c48806499 completed April 20, 2026, 5:36 p.m.
Created at: April 11, 2026, 3:40 p.m.