Triple

T2483046
Position Surface form Disambiguated ID Type / Status
Subject Lake Bourget E55862 entity
Predicate hasShoreSettlement P16159 FINISHED
Object Chindrieux
Chindrieux is a commune in the Savoie department of southeastern France, known for its lakeside location near Lake Bourget and its scenic Alpine surroundings.
E274662 NE FINISHED

How this triple was built (4 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: Chindrieux | Statement: [Lake Bourget, hasShoreSettlement, Chindrieux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chindrieux
Context triple: [Lake Bourget, hasShoreSettlement, Chindrieux]
  • A. Chénas
    Chénas is a French appellation in the Beaujolais wine region known for producing structured, age-worthy red wines primarily from the Gamay grape.
  • B. Choully
    Choully is a small wine-producing village in the commune of Satigny in the canton of Geneva, Switzerland.
  • C. Doncieux
    Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
  • D. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • E. Choulex
    Choulex is a small municipality in the canton of Geneva in southwestern Switzerland, known for its rural character and proximity to the city of Geneva.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Chindrieux
Triple: [Lake Bourget, hasShoreSettlement, Chindrieux]
Generated description
Chindrieux is a commune in the Savoie department of southeastern France, known for its lakeside location near Lake Bourget and its scenic Alpine surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Chindrieux
Target entity description: Chindrieux is a commune in the Savoie department of southeastern France, known for its lakeside location near Lake Bourget and its scenic Alpine surroundings.
  • A. Chénas
    Chénas is a French appellation in the Beaujolais wine region known for producing structured, age-worthy red wines primarily from the Gamay grape.
  • B. Choully
    Choully is a small wine-producing village in the commune of Satigny in the canton of Geneva, Switzerland.
  • C. Doncieux
    Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
  • D. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • E. Choulex
    Choulex is a small municipality in the canton of Geneva in southwestern Switzerland, known for its rural character and proximity to the city of Geneva.
  • F. None of above. chosen

Provenance (5 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd163378481908b75f2f5de0e89c6 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b8021e08190a9197659387ec4f8 completed March 9, 2026, 8:20 p.m.
NEDg Description generation batch_69af41aa199c8190b4478a93c41ae18a completed March 9, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_69af4277601c8190b55d5c5504dcd0ab completed March 9, 2026, 9:58 p.m.
Created at: March 6, 2026, 9:45 p.m.