Triple

T21952063
Position Surface form Disambiguated ID Type / Status
Subject Quiz Show E542092 entity
Predicate cinematographer P1953 FINISHED
Object Michael Ballhaus 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: Michael Ballhaus | Statement: [Quiz Show, cinematographer, Michael Ballhaus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Ballhaus
Context triple: [Quiz Show, cinematographer, Michael Ballhaus]
  • A. Michael Ballhaus chosen
    Michael Ballhaus was a renowned German cinematographer celebrated for his dynamic camera work and frequent collaborations with director Martin Scorsese.
  • B. Michael Bruhn
    Michael Bruhn is a person notable enough to be recognized as a namesake of the surname Bruhn, though specific widely known public details about him are not clearly established.
  • C. Paul Weinert
    Paul Weinert was a United States Army soldier and Medal of Honor recipient recognized for his bravery during the Indian Wars.
  • D. Michael Bollner
    Michael Bollner is a German former child actor best known for playing Augustus Gloop in the 1971 film "Willy Wonka & the Chocolate Factory."
  • E. Paul Zimmerer
    Paul Zimmerer was an American entrepreneur best known as the founder of Lindsay Corporation, a major manufacturer of agricultural irrigation and infrastructure equipment.
  • 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_69e0c47ef0e48190a50e1bcc43f4b3fd completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1243c84d4819097f5a93b128f024b completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:58 p.m.