Triple

T1292561
Position Surface form Disambiguated ID Type / Status
Subject Active Cosmetics Division E27578 entity
Predicate brandPortfolioIncludes P18121 FINISHED
Object Vichy E1394 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: Vichy | Statement: [Active Cosmetics Division, brandPortfolioIncludes, Vichy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vichy
Context triple: [Active Cosmetics Division, brandPortfolioIncludes, Vichy]
  • A. Vichy chosen
    Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
  • B. Thoiry
    Thoiry is a commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • C. Limoges
    Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
  • D. Évian-les-Bains
    Évian-les-Bains is a French spa and resort town in the Alps renowned worldwide for its mineral water and scenic lakeside setting.
  • E. Gonesse
    Gonesse is a commune in the northeastern suburbs of Paris, France, known historically as a rural town and now as part of the greater Paris metropolitan area.
  • 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_69a496d4ec448190ad653b2590c46711 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c48bec548190b25d4a74b323cc1b completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad231d1bdc8190bceaafcf86544bf1 completed March 8, 2026, 7:19 a.m.
Created at: March 1, 2026, 7:51 p.m.