Triple

T11913287
Position Surface form Disambiguated ID Type / Status
Subject Savoie department E283447 entity
Predicate subprefecture P9697 FINISHED
Object Albertville E82950 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: Albertville | Statement: [Savoie department, subprefecture, Albertville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albertville
Context triple: [Savoie department, subprefecture, Albertville]
  • A. Albertville chosen
    Albertville is a town in southeastern France best known internationally for hosting the 1992 Winter Olympics.
  • B. Albertville
    Albertville is the former colonial name of the city now known as Kalemie, located on the western shore of Lake Tanganyika in the Democratic Republic of the Congo.
  • C. Unienville
    Unienville is a small commune in the Aube department of north-central France.
  • D. Florenville
    Florenville is a picturesque town in southern Belgium’s Wallonia region, known for its scenic setting along the Semois River and surrounding Ardennes landscapes.
  • E. Thorntonville
    Thorntonville is a small town located in Ward County in western Texas, United States.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e528f6748190ac873a040a61fa93 completed April 10, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4185fd3588190807cc2906c4ce3fd completed May 1, 2026, 3:05 a.m.
Created at: April 8, 2026, 9:44 p.m.