Triple

T5832703
Position Surface form Disambiguated ID Type / Status
Subject Peugeot Sport E129388 entity
Predicate brand P1500 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 Sport, brand, Peugeot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peugeot
Context triple: [Peugeot Sport, brand, 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_69c0084af79c81908af128ccc29983d0 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0346c331c8190bac050d425961485 completed March 22, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c14127afdc8190a3deb020133ad894 completed March 23, 2026, 1:33 p.m.
Created at: March 22, 2026, 3:54 p.m.