Triple

T10364267
Position Surface form Disambiguated ID Type / Status
Subject Nordisk Film E244212 entity
Predicate hasSubsidiary P254 FINISHED
Object Nordisk Film Distribution E244212 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: Nordisk Film Distribution | Statement: [Nordisk Film, hasSubsidiary, Nordisk Film Distribution]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordisk Film Distribution
Context triple: [Nordisk Film, hasSubsidiary, Nordisk Film Distribution]
  • A. Nordisk Film chosen
    Nordisk Film is a major Danish entertainment company and one of the world’s oldest film studios, known for producing and distributing films across the Nordic region.
  • B. Tobis Film
    Tobis Film is a German film production and distribution company known for its role in the European cinema industry since the early 20th century.
  • C. Svensk Filmindustri
    Svensk Filmindustri is a major Swedish film production and distribution company, historically one of the country’s most influential studios.
  • D. Argos Films
    Argos Films is a French film production company known for producing influential art-house and auteur cinema.
  • E. Benaroya Pictures
    Benaroya Pictures is an independent film production company known for financing and producing a range of critically acclaimed and commercially successful feature films.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e964a53c8190b748e80850e96656 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d750c2d2748190b871b928d5a094f8 completed April 9, 2026, 7:09 a.m.
Created at: April 6, 2026, noon