Triple

T10533700
Position Surface form Disambiguated ID Type / Status
Subject Chevrier E248508 entity
Predicate associatedWithRegion P285 FINISHED
Object Bordeaux E626161 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: Bordeaux | Statement: [Chevrier, associatedWithRegion, Bordeaux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bordeaux
Context triple: [Chevrier, associatedWithRegion, Bordeaux]
  • A. Bordeaux chosen
    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.
  • B. Bordeaux
    Bordeaux is a renowned wine-producing region in southwestern France, famous for its prestigious red blends and long winemaking tradition.
  • C. Bordeaux
    Bordeaux is a popular See's Candies confection, typically a creamy brown sugar–butter center coated in chocolate and topped with chocolate sprinkles.
  • D. 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.
  • E. Toulouse
    Toulouse is a major city in southwestern France known for its aerospace industry, historic pink-brick architecture, and vibrant university and cultural life.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a19b59c8190b00db7d5813ad37d completed April 7, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95e5d1a2c81908a9bb8f1c55414fa completed April 10, 2026, 8:32 p.m.
Created at: April 6, 2026, 12:31 p.m.