Triple

T12563980
Position Surface form Disambiguated ID Type / Status
Subject Schneider E295419 entity
Predicate notableBearersInclude P2531 FINISHED
Object Helge Schneider E442037 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: Helge Schneider | Statement: [Schneider, notableBearersInclude, Helge Schneider]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helge Schneider
Context triple: [Schneider, notableBearersInclude, Helge Schneider]
  • A. Helge Schneider chosen
    Helge Schneider is a German comedian, musician, actor, and author known for his absurdist humor, improvisational jazz performances, and cult status in German-speaking entertainment.
  • B. Benno Elbs
    Benno Elbs is an Austrian Roman Catholic prelate who serves as the bishop of the Diocese of Feldkirch.
  • C. Klaus Menzel
    Klaus Menzel is a notable individual who shares the surname Menzel, recognized enough to be specifically distinguished among bearers of the name.
  • D. Hans Goerke
    Hans Goerke was the original owner and namesake of the historic Goerke House.
  • E. Klaus Maria Brandauer
    Klaus Maria Brandauer is an acclaimed Austrian actor and director known internationally for his intense, charismatic performances in films such as "Out of Africa" and "Mephisto."
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d95494ae1c81908b9ee14b8ef92a65 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6558da7e0819086860bfaf394e2d8 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 11:49 p.m.