Triple

T1888976
Position Surface form Disambiguated ID Type / Status
Subject Louis Vuitton Foundation E41824 entity
Predicate sponsor P67 FINISHED
Object LVMH E72279 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: LVMH | Statement: [Louis Vuitton Foundation, sponsor, LVMH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LVMH
Context triple: [Louis Vuitton Foundation, sponsor, LVMH]
  • A. LVMH chosen
    LVMH is a French multinational luxury conglomerate that owns a wide portfolio of prestigious brands across fashion, jewelry, cosmetics, wines, and spirits.
  • B. 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.
  • C. Hermès International
    Hermès International is a French luxury goods manufacturer renowned for its high-end leather goods, fashion accessories, and ready-to-wear collections.
  • D. Richemont
    Richemont is a Swiss-based luxury goods holding company that owns a portfolio of prestigious brands in jewelry, watches, fashion, and accessories.
  • E. Louis Vuitton
    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.
  • 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_69a8864b6de0819098d089f6a1b910a7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb142e41881908fc7335673a9dec3 completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3cc8d5c8190bee638183989830c completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:34 p.m.