Triple

T20997495
Position Surface form Disambiguated ID Type / Status
Subject Nightwatching E517186 entity
Predicate distributor P1951 FINISHED
Object ContentFilm 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: ContentFilm | Statement: [Nightwatching, distributor, ContentFilm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ContentFilm
Context triple: [Nightwatching, distributor, ContentFilm]
  • A. ContentFilm chosen
    ContentFilm is a film production and distribution company known for backing independent and critically acclaimed movies such as "Thank You for Smoking."
  • B. FilmFour
    FilmFour is a British film production company and former television channel associated with Channel 4, known for backing distinctive independent and arthouse films.
  • C. VideoFilmes
    VideoFilmes is a Brazilian film production company known for its work on acclaimed art-house and independent films.
  • D. FilmScene cinema
    FilmScene cinema is an independent, nonprofit movie theater and film arts organization known for showcasing arthouse, foreign, and documentary films in Iowa City, Iowa.
  • E. Flims
    Flims is a Swiss alpine resort village in the canton of Graubünden, known for its skiing, hiking, and scenic mountain landscapes.
  • 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_69e0b5006e2881909fc2383f841740cc completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc22ca6081908bf054ddcfea9e19 completed April 21, 2026, 4:25 a.m.
Created at: April 16, 2026, 1:51 p.m.