Triple

T29473955
Position Surface form Disambiguated ID Type / Status
Subject Alpha 60 E747589 entity
Predicate hasCinematicStyleContext P41012 FINISHED
Object black-and-white cinematography 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: black-and-white cinematography | Statement: [Alpha 60, hasCinematicStyleContext, black-and-white cinematography]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCinematicStyleContext
Context triple: [Alpha 60, hasCinematicStyleContext, black-and-white cinematography]
  • A. hasCinematicFeature
    Indicates that something possesses a specific cinematic characteristic, quality, or element related to film or visual storytelling.
  • B. hasCinematicThemes
    Indicates that something incorporates or is characterized by themes, motifs, or stylistic elements commonly associated with cinema or film.
  • C. hasTheatricalStyle
    Indicates that one entity possesses, exhibits, or is characterized by a particular theatrical style associated with another entity.
  • D. hasFilmStyle chosen
    Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
  • E. cinematicContext
    Indicates the relationship in which something is situated within, shaped by, or relevant to the circumstances, style, or conventions of cinema or 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_69f0bd42cf308190bb01b20bc5b7c2d0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f70e8755a48190931eaa77946f9460 completed May 3, 2026, 8:59 a.m.
PD Predicate disambiguation batch_69f70abc00848190a1c3f495ef6c8dc6 completed May 3, 2026, 8:43 a.m.
Created at: April 28, 2026, 3:59 p.m.