Triple

T12528880
Position Surface form Disambiguated ID Type / Status
Subject Rut Brandt E299507 entity
Predicate relative P37 FINISHED
Object Matthias Brandt E364894 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: Matthias Brandt | Statement: [Rut Brandt, relative, Matthias Brandt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthias Brandt
Context triple: [Rut Brandt, relative, Matthias Brandt]
  • A. Matthias Brandt chosen
    Matthias Brandt is a German actor and the son of former German chancellor Willy Brandt.
  • B. Matthias Butz
    Matthias Butz is an individual notable enough to be specifically cited as a bearer of the surname Butz.
  • C. Christian Brandauer
    Christian Brandauer is the son of Austrian actor and director Klaus Maria Brandauer.
  • D. Matthias Koenigswieser
    Matthias Koenigswieser is a cinematographer known for his work on feature films such as the live-action Disney movie "Christopher Robin."
  • E. Matthias Zell
    Matthias Zell was a leading early Protestant reformer and preacher in Strasbourg who played a central role in introducing and spreading Reformation ideas in the city.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545e90948190980bd4d64964a0f2 completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0d6947c819080d33199d331724c completed May 3, 2026, 3:28 a.m.
Created at: April 8, 2026, 9:57 p.m.