Triple

T18819783
Position Surface form Disambiguated ID Type / Status
Subject DKNY E460233 entity
Predicate hasLogoText P3623 FINISHED
Object DKNY 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: DKNY | Statement: [DKNY, hasLogoText, DKNY]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DKNY
Context triple: [DKNY, hasLogoText, DKNY]
  • A. DKNY chosen
    DKNY is a New York-based fashion brand founded by Donna Karan, known for its contemporary, urban-inspired clothing and accessories.
  • B. Calvin Klein
    Calvin Klein is an American fashion brand renowned for its minimalist aesthetic, iconic underwear and denim lines, and influential advertising campaigns.
  • C. DKNY (licensed watches)
    DKNY (licensed watches) is a line of fashion-forward timepieces produced under license by Fossil Group for the New York–based lifestyle brand DKNY.
  • D. New York & Company
    New York & Company is an American specialty retailer known for offering women's fashion apparel and accessories, particularly career and casual wear, through mall-based stores and online channels.
  • E. Esprit
    Esprit is an international fashion brand known for its casual, contemporary clothing and lifestyle products.
  • 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.