Triple

T18819745
Position Surface form Disambiguated ID Type / Status
Subject DKNY E460233 entity
Predicate foundedBy P104 FINISHED
Object Donna Karan 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: Donna Karan | Statement: [DKNY, foundedBy, Donna Karan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donna Karan
Context triple: [DKNY, foundedBy, Donna Karan]
  • A. Donna Karan chosen
    Donna Karan is an influential American fashion designer best known for founding the DKNY label and redefining modern women’s workwear with her sleek, versatile designs.
  • B. Diane von Fürstenberg
    Diane von Fürstenberg is a Belgian-born fashion designer best known for creating the iconic wrap dress and founding her eponymous global luxury brand.
  • C. Carolina Herrera
    Carolina Herrera is a Venezuelan-American fashion designer renowned for her elegant, sophisticated clothing and fragrance lines favored by celebrities and socialites.
  • D. Cynthia Rowley
    Cynthia Rowley is an American fashion designer known for her playful, colorful, and adventurous ready-to-wear and accessories collections.
  • E. Betsey Johnson
    Betsey Johnson is an American fashion designer known for her whimsical, colorful, and exuberant clothing designs and her playful, cartwheeling runway finales.
  • 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_69d8dcf94c288190a06dea029ae4b223 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5a6b8b7d88190a8828746176776ea completed April 20, 2026, 4:08 a.m.
Created at: April 10, 2026, 11:55 a.m.