Triple

T8489338
Position Surface form Disambiguated ID Type / Status
Subject Iveco E200926 entity
Predicate brand P1500 FINISHED
Object Magirus E212631 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: Magirus | Statement: [Iveco, brand, Magirus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magirus
Context triple: [Iveco, brand, Magirus]
  • A. Hella
    Hella is a central character in James Baldwin’s novel "Giovanni’s Room," serving as the protagonist’s fiancée and a key figure in exploring themes of sexuality, identity, and societal expectations.
  • B. Spragga Benz
    Spragga Benz is a prominent Jamaican dancehall deejay known for his influential 1990s hits and collaborations across reggae, hip hop, and international pop music.
  • C. Bernmobil
    Bernmobil is the public transport company responsible for operating trams, buses, and other urban transit services in the Swiss city of Bern.
  • D. Neoplan chosen
    Neoplan is a German bus and coach manufacturer renowned for its innovative, high-end touring and city buses.
  • E. Schmitz
    Schmitz is one of the two manipulative arsonists who infiltrate the bourgeois household in Max Frisch’s play "Biedermann und die Brandstifter."
  • 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_69ca831d7b148190a6e32c1de43ab13b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5581d308190b47d76dd49a36529 completed March 31, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4df197c48190812c5287119e5528 completed April 2, 2026, 11:07 a.m.
Created at: March 30, 2026, 6:13 p.m.