Triple

T10047713
Position Surface form Disambiguated ID Type / Status
Subject Candice Swanepoel E207658 entity
Predicate hasModeledFor P17880 FINISHED
Object Jason Wu E836680 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: Jason Wu | Statement: [Candice Swanepoel, hasModeledFor, Jason Wu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jason Wu
Context triple: [Candice Swanepoel, hasModeledFor, Jason Wu]
  • A. Jason Wu chosen
    Jason Wu is a Taiwanese-Canadian fashion designer renowned for his elegant, modern womenswear and for dressing high-profile figures including former U.S. First Lady Michelle Obama.
  • B. Alexander Wang
    Alexander Wang is an American fashion designer known for his edgy, minimalist aesthetic and influential work at his eponymous label and as former creative director of Balenciaga.
  • C. Guo Pei
    Guo Pei is a renowned Chinese haute couture fashion designer celebrated globally for her elaborate, sculptural gowns and fusion of traditional Chinese craftsmanship with contemporary luxury.
  • D. Vera Wang
    Vera Wang is an American fashion designer renowned for her luxury bridal gowns and influential eveningwear collections.
  • E. Alexandr Wang
    Alexandr Wang is an American entrepreneur best known as the co-founder and CEO of AI data company Scale AI.
  • 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_69ca835ad0608190b7c80b292da004f5 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf664dd881908786fcd802bf10da completed April 2, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a4064a48190b4fdb6bf3ea5af05 completed April 5, 2026, 5:22 p.m.
Created at: March 30, 2026, 8:56 p.m.