Triple

T5064739
Position Surface form Disambiguated ID Type / Status
Subject Peugeot 607 E114115 entity
Predicate manufacturer P490 FINISHED
Object Peugeot E16307 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: Peugeot | Statement: [Peugeot 607, manufacturer, Peugeot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peugeot
Context triple: [Peugeot 607, manufacturer, Peugeot]
  • A. Peugeot chosen
    Peugeot is a historic French automobile manufacturer known for producing a wide range of passenger cars and commercial vehicles, now operating as a core brand within the multinational automotive group Stellantis.
  • B. Renault
    Renault is a major French automobile manufacturer known for producing a wide range of passenger cars, commercial vehicles, and electric vehicles sold worldwide.
  • C. Citroën
    Citroën is a historic French automobile manufacturer known for its innovative engineering and distinctive car designs.
  • D. Peugeot Partner
    The Peugeot Partner is a compact panel van and leisure activity vehicle produced by the French automaker Peugeot, widely used for both commercial and family transport.
  • E. Peugeot Sport
    Peugeot Sport is the motorsport arm of French automaker Peugeot, responsible for designing, developing, and running the brand’s racing programs in disciplines such as rallying, endurance racing, and touring cars.
  • 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_69bd443c0c8c81908663b77afb28e165 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7478f7988190bc0473e8af055147 completed March 20, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea49ae8c081908ef8c2e2dbbe3b49 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:38 p.m.