Triple

T12009762
Position Surface form Disambiguated ID Type / Status
Subject SKA Films E285875 entity
Predicate alternativeName P39 FINISHED
Object Ska Films E285875 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: Ska Films | Statement: [SKA Films, alternativeName, Ska Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ska Films
Context triple: [SKA Films, alternativeName, Ska Films]
  • A. SKA Films chosen
    SKA Films is a British film production company co-founded by director Matthew Vaughn, known for producing stylish crime and action movies such as "Layer Cake."
  • B. Skreba Films
    Skreba Films is a film production company known for producing the biographical drama "Tom & Viv."
  • C. Scion Films
    Scion Films is a British film production company known for backing acclaimed dramas such as "The Constant Gardener."
  • D. See-Saw Films
    See-Saw Films is a British-Australian film and television production company known for acclaimed works such as the Academy Award–winning drama "The King’s Speech."
  • E. Shoebox Films
    Shoebox Films is a British film production company known for producing independent and auteur-driven movies, including the 2019 thriller "Serenity."
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903d61a4c81909e6cb6500b61df94 completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f642801881909a94d67c99bfd110 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:46 p.m.