Triple

T10215424
Position Surface form Disambiguated ID Type / Status
Subject Massif des Bauges E242427 entity
Predicate nearCity P350 FINISHED
Object Annecy E410098 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: Annecy | Statement: [Massif des Bauges, nearCity, Annecy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Annecy
Context triple: [Massif des Bauges, nearCity, Annecy]
  • A. Annecy chosen
    Annecy is a picturesque city in southeastern France, known for its medieval old town, canals, and lakeside setting in the French Alps.
  • B. Thonon-les-Bains
    Thonon-les-Bains is a French spa and resort town in the Haute-Savoie region, known for its lakeside setting on Lake Geneva and views of the Alps.
  • C. Briançon
    Briançon is a fortified alpine town in southeastern France, known as one of the highest cities in Europe and a key historical stronghold near the Italian border.
  • D. Nyons
    Nyons is a small town in southeastern France renowned for its olive production and picturesque setting in the Drôme Provençale region.
  • E. Annecy agglomeration
    Annecy agglomeration is an urban area in southeastern France centered on the city of Annecy, known for its lakeside setting, Alpine surroundings, and role as a regional economic and cultural hub.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa2894d0819095704449ecc2db6c completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d74fd5df188190b5ad2e57abeb6b13 completed April 9, 2026, 7:05 a.m.
Created at: April 6, 2026, 11:04 a.m.