Triple

T8580053
Position Surface form Disambiguated ID Type / Status
Subject Mischa Spoliansky E203146 entity
Predicate employer P7 FINISHED
Object UFA GmbH E355973 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: UFA GmbH | Statement: [Mischa Spoliansky, employer, UFA GmbH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UFA GmbH
Context triple: [Mischa Spoliansky, employer, UFA GmbH]
  • A. 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.
  • B. UFA
    UFA is the acronym for the Uniformed Firefighters Association, the labor union representing New York City’s rank-and-file firefighters.
  • C. 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.
  • D. Global Entertainment Productions GmbH & Co. Medien KG
    Global Entertainment Productions GmbH & Co. Medien KG is a German film and media production company involved in the creation and financing of motion pictures such as the thriller "8MM."
  • E. Intertainment AG
    Intertainment AG is a German media and film licensing company known for financing and distributing Hollywood movies in international markets.
  • 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_69ca8328ebe481909a8c038fa79959b4 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbeb1a026c819089183f542eeb7837 completed March 31, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce89ae87f08190b83bc539e1d4eeaa completed April 2, 2026, 3:22 p.m.
Created at: March 30, 2026, 6:22 p.m.