Triple

T3107697
Position Surface form Disambiguated ID Type / Status
Subject Savoie E64871 entity
Predicate wineRegion P6176 FINISHED
Object Vin de Savoie E64871 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: Vin de Savoie | Statement: [Savoie, wineRegion, Vin de Savoie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vin de Savoie
Context triple: [Savoie, wineRegion, Vin de Savoie]
  • A. Savoie chosen
    Savoie is a mountainous department in southeastern France, known for its Alpine landscapes, ski resorts, and rich Savoyard cultural heritage.
  • B. Riviera vaudoise
    Riviera vaudoise is a picturesque region along the northeastern shore of Lake Geneva in the canton of Vaud, Switzerland, known for its vineyards, lakeside towns, and mild microclimate.
  • C. Drôme
    Drôme is a department in southeastern France known for its diverse landscapes, historic towns, and location between the Alps and the Rhône Valley.
  • D. Mâconnais
    Mâconnais is a wine-producing subregion in southern Burgundy, France, best known for its Chardonnay-based white wines.
  • E. Haute-Savoie
    Haute-Savoie is a department in the Auvergne-Rhône-Alpes region of southeastern France, renowned for its Alpine landscapes, ski resorts, and proximity to Mont Blanc and the Swiss and Italian borders.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada29d4aa8819093287bc71370fc05 completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f5994088190abc4b56040922c16 completed March 12, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:04 p.m.