Triple

T1903658
Position Surface form Disambiguated ID Type / Status
Subject Scania E37748 entity
Predicate parentCompany P254 FINISHED
Object Traton E38078 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: Traton | Statement: [Scania, parentCompany, Traton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Traton
Context triple: [Scania, parentCompany, Traton]
  • A. Traton chosen
    Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
  • B. Suter
    Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
  • C. Renault
    Renault is a major French automobile manufacturer known for producing a wide range of passenger cars, commercial vehicles, and electric vehicles sold worldwide.
  • D. Peugeot
    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.
  • E. Renault–Gitane
    Renault–Gitane was a dominant French professional cycling team of the late 1970s and early 1980s, known for nurturing multiple Grand Tour champions and pioneering modern team tactics.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1909aec8190b3259c8f969ce81e completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaf768888190885ffa1632537445 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:35 p.m.