Triple

T7534394
Position Surface form Disambiguated ID Type / Status
Subject Avenue Montaigne E178109 entity
Predicate hasShop P23299 FINISHED
Object Louis Vuitton E58476 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: Louis Vuitton | Statement: [Avenue Montaigne, hasShop, Louis Vuitton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis Vuitton
Context triple: [Avenue Montaigne, hasShop, Louis Vuitton]
  • A. Louis Vuitton chosen
    Louis Vuitton is a French luxury fashion house and brand renowned worldwide for its high-end leather goods, ready-to-wear, accessories, and iconic monogram designs.
  • B. Loewe
    Loewe is a Spanish luxury fashion house renowned for its high-end leather goods, ready-to-wear, and accessories.
  • C. Gucci
    Gucci is a renowned Italian luxury fashion house known for its high-end clothing, accessories, and iconic branding.
  • D. Lanvin
    Lanvin is a historic French luxury fashion house, founded in 1889 by Jeanne Lanvin, renowned for its elegant haute couture and ready-to-wear collections.
  • E. Kering
    Kering is a French multinational luxury group that owns and manages high-end fashion and leather goods brands such as Gucci, Saint Laurent, and Bottega Veneta.
  • 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_69c69f2acdbc8190b5a8320168c1d0ba completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f84a9d28819084ebfc44fcb2c29c completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84f0765b48190b8df68f22c8901f4 completed March 28, 2026, 9:58 p.m.
Created at: March 27, 2026, 3:47 p.m.