Triple

T5563948
Position Surface form Disambiguated ID Type / Status
Subject Balagne dialect E145833 entity
Predicate spokenIn P2266 FINISHED
Object Balagne E427363 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: Balagne | Statement: [Balagne dialect, spokenIn, Balagne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balagne
Context triple: [Balagne dialect, spokenIn, Balagne]
  • A. Balagne chosen
    Balagne is a picturesque region in northwestern Corsica, France, known for its coastal towns, hilltop villages, and Mediterranean landscapes.
  • B. Gueugnon
    Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
  • C. Léognan
    Léognan is a renowned wine-producing commune in southwestern France, celebrated for its prestigious red and white Bordeaux wines.
  • D. Peisey-Vallandry
    Peisey-Vallandry is a French Alpine ski resort and traditional mountain village area in the Savoie region, known for its access to the Paradiski ski domain.
  • E. Saignelégier
    Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
  • 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_69c008fdae24819081aa002ad99cd966 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02032330c819094f2bc1e8c93a5b6 completed March 22, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d0ca0088190a5d63139ba194e8e completed March 22, 2026, 8:11 p.m.
Created at: March 22, 2026, 3:36 p.m.