Triple

T12454211
Position Surface form Disambiguated ID Type / Status
Subject Bangert E297611 entity
Predicate hasNotableBearer P458 FINISHED
Object Schultes Bangert E297613 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: Schultes Bangert | Statement: [Bangert, hasNotableBearer, Schultes Bangert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schultes Bangert
Context triple: [Bangert, hasNotableBearer, Schultes Bangert]
  • A. Schultes chosen
    Schultes is a member of the Bangert, Jansen, Scholz, Schultes group, likely a professional or academic collective named after its principal participants.
  • B. Rattenberg
    Rattenberg is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany, known for its rural setting and traditional Bavarian character.
  • C. Die Bertinis
    Die Bertinis is a German television miniseries based on Ralph Giordano’s semi-autobiographical novel about a Jewish-Italian family in Hamburg during the Nazi era.
  • D. Brechtel
    Brechtel is a residential subarea within the Algiers neighborhood of New Orleans, Louisiana.
  • E. El Brendel
    El Brendel was an American vaudeville and film comedian best known for his faux-Swedish accent and comic relief roles in early Hollywood talkies.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94da0b5988190b9df26dd3bb87337 completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f190c788190adceaab8117d52a6 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:56 p.m.