Triple

T8625437
Position Surface form Disambiguated ID Type / Status
Subject Man with a Movie Camera E204268 entity
Predicate metaCinematicElement P61780 FINISHED
Object film about filmmaking LITERAL 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: film about filmmaking | Statement: [Man with a Movie Camera, metaCinematicElement, film about filmmaking]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: metaCinematicElement
Context triple: [Man with a Movie Camera, metaCinematicElement, film about filmmaking]
  • A. cinematicContext chosen
    Indicates the relationship in which something is situated within, shaped by, or relevant to the circumstances, style, or conventions of cinema or film.
  • B. cinematicSignificance
    Indicates the degree to which something holds notable importance, influence, or impact within the realm of cinema or film history.
  • C. featuresMidCreditsScene
    Indicates that the work includes a special scene or content that appears during the middle of the closing credits.
  • D. hasCinematicThemes
    Indicates that something incorporates or is characterized by themes, motifs, or stylistic elements commonly associated with cinema or film.
  • E. filmicFunction
    Indicates the role or purpose that something serves within the structure, style, or narrative function of a film.
  • F. None of above.

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_69ca834a4ea0819094970dceb9e389f3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5730309081909a9a0256c9bf5f8f completed March 31, 2026, 11:22 p.m.
PD Predicate disambiguation batch_69cc455906f8819082edd79cb4a1cf28 completed March 31, 2026, 10:06 p.m.
Created at: March 30, 2026, 6:26 p.m.