Triple

T9952136
Position Surface form Disambiguated ID Type / Status
Subject Compagnie des chemins de fer du Midi E195354 entity
Predicate servedCity P3936 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: [Compagnie des chemins de fer du Midi, servedCity, Bordeaux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bordeaux
Context triple: [Compagnie des chemins de fer du Midi, servedCity, 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_69ca82e96a108190932bd1fc4acd73a0 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb6922f888190b5c4b58fbe21bea2 completed April 2, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3171f23d08190a5f9cd2c3d139a0e completed April 6, 2026, 2:14 a.m.
Created at: March 30, 2026, 8:46 p.m.