Triple

T17305917
Position Surface form Disambiguated ID Type / Status
Subject Charles Melton E420163 entity
Predicate modelingWorkFor P93910 FINISHED
Object MAC Cosmetics E894474 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: MAC Cosmetics | Statement: [Charles Melton, modelingWorkFor, MAC Cosmetics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MAC Cosmetics
Context triple: [Charles Melton, modelingWorkFor, MAC Cosmetics]
  • A. MAC Cosmetics chosen
    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.
  • B. Maybelline New York
    Maybelline New York is a major American cosmetics and beauty brand known worldwide for its mass-market makeup products.
  • C. Too Faced
    Too Faced is a popular cosmetics brand known for its playful, feminine packaging and trend-driven makeup products.
  • D. 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.
  • E. Rimmel
    Rimmel is a British cosmetics brand best known for its affordable makeup products and the slogan "Get the London Look."
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e438ff3ee08190ab4c44a22f86b38b completed April 19, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180e0c1b881908aa2b6b4d8ac04b6 completed May 11, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:43 a.m.