Triple

T10189466
Position Surface form Disambiguated ID Type / Status
Subject Université Savoie Mont Blanc E237994 entity
Predicate hasCampusIn P4623 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: [Université Savoie Mont Blanc, hasCampusIn, Annecy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Annecy
Context triple: [Université Savoie Mont Blanc, hasCampusIn, 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_69ca84de1b208190bf17bb305b002605 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded7d6fdc81908052866495b6574f completed April 2, 2026, 4:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f6e73a2881908563e9e6a02df944 completed April 9, 2026, 12:46 a.m.
Created at: March 30, 2026, 9:12 p.m.