Triple

T22767735
Position Surface form Disambiguated ID Type / Status
Subject Schrader E563172 entity
Predicate hasVariant P455 FINISHED
Object Schroeder 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: Schroeder | Statement: [Schrader, hasVariant, Schroeder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schroeder
Context triple: [Schrader, hasVariant, Schroeder]
  • A. Schroeder chosen
    Schroeder is a character from the Peanuts comic strip known for his serious devotion to playing the piano and his admiration for Beethoven.
  • B. Scheer
    Scheer is a German surname most notably associated with Reinhard Scheer, a high-ranking Imperial German Navy admiral during World War I.
  • C. Scheyer
    Scheyer is a surname most prominently associated with Jon Scheyer, the former Duke basketball star and current head coach of the Duke Blue Devils men's basketball team.
  • D. Sanders
    Sanders is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
  • E. Kurt Schröder
    Kurt Schröder was a German film composer known for scoring early 20th-century European films, including notable British historical dramas.
  • 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_69e24552e11c81909c2d61578a558bd7 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17a81d3348190b005a43a5e03d406 completed April 29, 2026, 3:26 a.m.
Created at: April 17, 2026, 3:27 p.m.