Triple

T11582489
Position Surface form Disambiguated ID Type / Status
Subject Chindrieux E274662 entity
Predicate locatedNear P294 FINISHED
Object Chambéry E46643 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: Chambéry | Statement: [Chindrieux, locatedNear, Chambéry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chambéry
Context triple: [Chindrieux, locatedNear, 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. Champéry
    Champéry is a Swiss alpine village and ski resort in the canton of Valais, known for its access to the Portes du Soleil ski area and mountain tourism.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8904db5748190ae5f10ae86ccdf46 completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69f69b76e0cc8190aa7303347e0183d4 completed May 3, 2026, 12:48 a.m.
Created at: April 8, 2026, 9:38 p.m.