Triple

T22263046
Position Surface form Disambiguated ID Type / Status
Subject Auvergne-Rhône-Alpes E550277 entity
Predicate majorCity P316 FINISHED
Object Chambéry NE NERFINISHED

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: Chambéry | Statement: [Auvergne-Rhône-Alpes, majorCity, Chambéry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chambéry
Context triple: [Auvergne-Rhône-Alpes, majorCity, Chambéry]
  • A. Chambéry chosen
    Chambéry is a historic city in southeastern France that served as the political and cultural center of the former Duchy of Savoy.
  • B. Grenoble
    Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
  • C. Aix-les-Bains
    Aix-les-Bains is a French spa and resort town in the Savoie department, renowned for its thermal baths and lakeside setting on the edge of the Alps.
  • D. 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.
  • E. Crissier
    Crissier is a municipality in the canton of Vaud in western Switzerland, located in the suburban area northwest of Lausanne.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e42adb8819087714772ea606709 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f141b94a688190b17c55477993a745 completed April 28, 2026, 11:24 p.m.
Created at: April 16, 2026, 8:39 p.m.