Triple

T22092339
Position Surface form Disambiguated ID Type / Status
Subject Parker E545941 entity
Predicate distributor P1951 FINISHED
Object FilmDistrict 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: FilmDistrict | Statement: [Parker, distributor, FilmDistrict]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FilmDistrict
Context triple: [Parker, distributor, FilmDistrict]
  • A. FilmDistrict chosen
    FilmDistrict was an American film distribution company known for releasing mid-budget genre and independent films in the early 2010s.
  • B. Film Booking Offices of America
    Film Booking Offices of America was an early 20th-century American film distribution and production company that became a key predecessor to the major Hollywood studio RKO Radio Pictures.
  • C. FilmStruck
    FilmStruck was a subscription-based streaming service specializing in classic, arthouse, and independent films, including titles from the Criterion Collection.
  • D. FilmRise
    FilmRise is an independent film and television distribution company known for acquiring and releasing a wide range of indie features, documentaries, and classic content across digital and traditional platforms.
  • E. Movie Central
    Movie Central was a Canadian premium television channel that specialized in airing movies and high-profile television series.
  • 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e6b1d881909bf0f4a52199354c completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.