Triple

T17455596
Position Surface form Disambiguated ID Type / Status
Subject Peugeot 104 E425018 entity
Predicate designCompany P25389 FINISHED
Object Pininfarina NE NERFINISHED

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: Pininfarina | Statement: [Peugeot 104, designCompany, Pininfarina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pininfarina
Context triple: [Peugeot 104, designCompany, Pininfarina]
  • A. Pininfarina chosen
    Pininfarina is an Italian design and engineering firm renowned for creating iconic car designs for brands such as Ferrari, Maserati, and Alfa Romeo.
  • B. Zagato
    Zagato is an Italian automotive design and coachbuilding firm renowned for its lightweight, aerodynamically styled sports and racing cars.
  • C. Bertone
    Bertone is an Italian surname most notably associated with Tarcisio Bertone, a prominent cardinal and former Vatican Secretary of State.
  • D. Bertone
    Bertone is an Italian automotive design and coachbuilding firm renowned for styling numerous iconic European cars.
  • E. Italdesign
    Italdesign is an Italian automotive design and engineering firm renowned for creating iconic car designs for major manufacturers worldwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45141e1d48190b7de9159f1fd71fa completed April 19, 2026, 3:51 a.m.
Created at: April 10, 2026, 5:47 a.m.