Triple

T1448772
Position Surface form Disambiguated ID Type / Status
Subject Courseulles-sur-Mer E31237 entity
Predicate department P1467 FINISHED
Object Calvados E105902 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: Calvados | Statement: [Courseulles-sur-Mer, department, Calvados]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calvados
Context triple: [Courseulles-sur-Mer, department, Calvados]
  • A. Calvados chosen
    Calvados is a department in the Normandy region of northwestern France, known for its historic D-Day landing beaches and production of the apple brandy that shares its name.
  • B. Sauternes
    Sauternes is a renowned sweet white wine appellation in southwestern France, famous for its botrytized wines made primarily from Sémillon and Sauvignon Blanc grapes.
  • C. Champagne
    Champagne is a renowned wine-producing region in northeastern France famous for its sparkling wines made primarily from Chardonnay, Pinot Noir, and Pinot Meunier grapes.
  • D. Bourbon-l’Archambault
    Bourbon-l’Archambault is a historic spa town in central France known as the ancestral seat of the Bourbon dynasty.
  • E. Champenois
    Champenois is a Romance regional language historically spoken in parts of northeastern France and adjacent areas of Wallonia in Belgium.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c55c408c8190917ed44d9070a2fb completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08c229808190af9936b481390170 completed March 8, 2026, 5:27 a.m.
Created at: March 1, 2026, 8 p.m.