Triple

T4608495
Position Surface form Disambiguated ID Type / Status
Subject Bursins E100494 entity
Predicate region P40 FINISHED
Object La Côte E367062 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: La Côte | Statement: [Bursins, region, La Côte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Côte
Context triple: [Bursins, region, La Côte]
  • A. La Côte chosen
    La Côte is a wine-producing region along the northern shore of Lake Geneva in the canton of Vaud, Switzerland, known for its picturesque vineyards and small towns.
  • B. The Riviera
    The Riviera is an affluent residential neighborhood in Los Angeles’ Pacific Palisades known for its luxury homes, exclusive country club, and proximity to the Santa Monica Mountains and Pacific Ocean.
  • C. Fontenais
    Fontenais is a municipality in the canton of Jura in northwestern Switzerland, situated in the Ajoie region near the town of Porrentruy.
  • D. Pays de Cocagne
    Pays de Cocagne is a historic rural region in southwestern France famed for its past wealth from pastel (woad) cultivation and its idyllic, prosperous countryside image.
  • E. Entre-Deux-Mers
    Entre-Deux-Mers is a wine-producing subregion of Bordeaux in southwestern France, known primarily for its dry white wines.
  • 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_69bd43cce1e08190a07d53af6a9b6c24 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd599debdc81909d11d0e871c666bb completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03521a9481908073d50221c80d63 completed March 21, 2026, 2:32 a.m.
Created at: March 20, 2026, 1:12 p.m.