Triple

T21752063
Position Surface form Disambiguated ID Type / Status
Subject Bettencourt affair E536938 entity
Predicate location P40 FINISHED
Object Bordeaux 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: Bordeaux | Statement: [Bettencourt affair, location, Bordeaux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bordeaux
Context triple: [Bettencourt affair, location, Bordeaux]
  • A. Bordeaux chosen
    Bordeaux is a renowned wine-producing region in southwestern France, famous for its prestigious red blends and long winemaking tradition.
  • B. Bordeaux
    Bordeaux is a popular See's Candies confection, typically a creamy brown sugar–butter center coated in chocolate and topped with chocolate sprinkles.
  • C. Bordeaux
    Bordeaux is a residential neighborhood in the Ahuntsic-Cartierville borough of Montreal, Quebec, known for its riverside location along the Rivière des Prairies and its mix of parks and urban amenities.
  • D. Burdeos
    Burdeos is a coastal municipality located on Polillo Island in the province of Quezon, Philippines, known for its fishing communities and island landscapes.
  • E. Nantes
    Nantes is a historic port city in western France on the Loire River, known for its maritime heritage, cultural institutions, and vibrant arts scene.
  • 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_69e0c46eab808190b848242d63a17c47 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01d8a6d4881908cc69e7247cce3a5 completed April 28, 2026, 2:38 a.m.
Created at: April 16, 2026, 6:50 p.m.