Triple

T13716782
Position Surface form Disambiguated ID Type / Status
Subject Soviet film industry E328922 entity
Predicate hasPart P35 FINISHED
Object Gorky Film Studio E801543 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: Gorky Film Studio | Statement: [Soviet film industry, hasPart, Gorky Film Studio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gorky Film Studio
Context triple: [Soviet film industry, hasPart, Gorky Film Studio]
  • A. Gorky Film Studio chosen
    Gorky Film Studio is a major Soviet and Russian film studio, historically known for producing children’s films and notable cinematic works in Moscow.
  • B. Mosfilm
    Mosfilm is one of Russia’s largest and oldest film studios, renowned for producing many of the Soviet Union’s most iconic movies.
  • 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. Goskino
    Goskino was the Soviet state film committee responsible for overseeing and producing motion pictures in the USSR, including landmark works of early Soviet cinema.
  • E. Gerasimov Institute of Cinematography
    The Gerasimov Institute of Cinematography is a renowned Russian film school in Moscow, considered one of the oldest and most prestigious institutions for cinema and television education in the world.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd4398f0448190810c840a82228706 completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a847c4d08190b05ea525059f0465 completed May 3, 2026, 7:55 p.m.
Created at: April 9, 2026, 9:54 p.m.