Triple

T19447422
Position Surface form Disambiguated ID Type / Status
Subject Werner R. Heymann E486515 entity
Predicate employer P7 FINISHED
Object UFA (Universum Film AG) 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: UFA (Universum Film AG) | Statement: [Werner R. Heymann, employer, UFA (Universum Film AG)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UFA (Universum Film AG)
Context triple: [Werner R. Heymann, employer, UFA (Universum Film AG)]
  • A. UFA film studios
    UFA film studios was a major German film production company that became a central force in shaping the innovative and influential cinema of the Weimar Republic.
  • B. Universum Film AG
    Universum Film AG (UFA) is a historic German film production and distribution company, especially prominent during the Weimar Republic era for its influential silent and early sound films.
  • C. UFA
    UFA is the acronym for the Uniformed Firefighters Association, the labor union representing New York City’s rank-and-file firefighters.
  • D. UFA chosen
    UFA (Universum Film AG) was a major German film production and distribution company, especially prominent during the Weimar Republic and early 20th-century cinema.
  • E. Mosfilm
    Mosfilm is one of Russia’s largest and oldest film studios, renowned for producing many of the Soviet Union’s most iconic movies.
  • 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6338b25d88190bc137a411576c73f completed April 20, 2026, 2:09 p.m.
Created at: April 10, 2026, 1:38 p.m.