Triple

T7036938
Position Surface form Disambiguated ID Type / Status
Subject Pierre Victurnien Vergniaud E163407 entity
Predicate workLocation P7 FINISHED
Object Bordeaux E6982 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: [Pierre Victurnien Vergniaud, workLocation, Bordeaux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bordeaux
Context triple: [Pierre Victurnien Vergniaud, workLocation, Bordeaux]
  • A. 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.
  • B. Bordeaux chosen
    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_69c6885e7c1c8190be32a8f79ab4e0cf completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e221a7988190b6b69782a275abb7 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8fa179c008190a6bba55cb62b7fe8 completed March 29, 2026, 10:08 a.m.
Created at: March 27, 2026, 2:36 p.m.