Triple

T20297667
Position Surface form Disambiguated ID Type / Status
Subject The Double Life of Véronique E505394 entity
Predicate hasCinematographicStyle P41012 FINISHED
Object lyrical 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: lyrical | Statement: [The Double Life of Véronique, hasCinematographicStyle, lyrical]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCinematographicStyle
Context triple: [The Double Life of Véronique, hasCinematographicStyle, lyrical]
  • A. hasFilmStyle chosen
    Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
  • B. hasTheatricalStyle
    Indicates that one entity possesses, exhibits, or is characterized by a particular theatrical style associated with another entity.
  • C. hasScreenplayStyle
    Indicates that an entity is associated with or characterized by a particular style or manner of screenplay writing.
  • D. cinematicForm
    Indicates that something is expressed, structured, or realized through the techniques, conventions, or medium of cinema or film.
  • E. hasCinematicThemes
    Indicates that something incorporates or is characterized by themes, motifs, or stylistic elements commonly associated with 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_69e0b4b8ab648190906e18538c250148 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e677095fb481909806214da4002b59 completed April 20, 2026, 6:57 p.m.
PD Predicate disambiguation batch_69e55b21b09081909e46691b6f45a07f completed April 19, 2026, 10:45 p.m.
Created at: April 16, 2026, 11:16 a.m.