Triple

T22022316
Position Surface form Disambiguated ID Type / Status
Subject Terminal (2018 film) E543873 entity
Predicate distributor P1951 FINISHED
Object Arrow Films 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: Arrow Films | Statement: [Terminal (2018 film), distributor, Arrow Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arrow Films
Context triple: [Terminal (2018 film), distributor, Arrow Films]
  • A. Arrow Films chosen
    Arrow Films is a British home video and film distribution company known for releasing cult, classic, and genre cinema in high-quality restored editions.
  • B. Alliance Films
    Alliance Films was a major Canadian film distribution and production company known for releasing a wide range of independent and international movies in Canada and other markets.
  • C. Palace Films
    Palace Films is an Australian film distribution company known for releasing a wide range of acclaimed international and local arthouse and independent films.
  • D. Icon Films
    Icon Films is a British television production company known for creating popular factual and wildlife documentary series, including the hit show "River Monsters."
  • E. Aries Films
    Aries Films is a film distribution company known for handling the release of independent and art-house movies such as "Bad Lieutenant."
  • 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_69e11e2e8ea4819084210fe06d3a1b8d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127c8ac6881909a9e96e0873a3ae2 completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:23 p.m.