Triple

T3233332
Position Surface form Disambiguated ID Type / Status
Subject Kendall Jenner E67792 entity
Predicate hasModeledFor P17880 FINISHED
Object Michael Kors E40456 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: Michael Kors | Statement: [Kendall Jenner, hasModeledFor, Michael Kors]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Kors
Context triple: [Kendall Jenner, hasModeledFor, Michael Kors]
  • A. Michael Kors chosen
    Michael Kors is an American fashion designer best known for his eponymous luxury brand specializing in ready-to-wear clothing, accessories, and handbags.
  • B. Nicole Miller
    Nicole Miller is an American fashion designer renowned for her modern, feminine womenswear and bold use of color and print.
  • C. David Lauren
    David Lauren is an American businessman and executive at the fashion company Ralph Lauren, founded by his father Ralph Lauren.
  • D. Ally Hilfiger
    Ally Hilfiger is an American artist, television personality, and fashion designer best known for starring in the MTV reality series "Rich Girls" and as the daughter of fashion designer Tommy Hilfiger.
  • E. Michele Lacroix
    Michele Lacroix is a Belgian public figure best known as the wife of professional footballer Kevin De Bruyne.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaedb718c8190aae12f763033713a completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2773b494c8190a2c0c5042e8eaa55 completed March 12, 2026, 8:20 a.m.
Created at: March 8, 2026, 3:08 p.m.