Triple

T35750279
Position Surface form Disambiguated ID Type / Status
Subject Dany Boon E1033300 entity
Predicate Bienvenue chez les Ch'tis_boxOffice P11911 FINISHED
Object one of the highest-grossing French films of all time 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: one of the highest-grossing French films of all time | Statement: [Dany Boon, Bienvenue chez les Ch'tis_boxOffice, one of the highest-grossing French films of all time]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: Bienvenue chez les Ch'tis_boxOffice
Context triple: [Dany Boon, Bienvenue chez les Ch'tis_boxOffice, one of the highest-grossing French films of all time]
  • A. cinemaOf
    Indicates a relationship where a cinema is associated with, belongs to, or is located within a particular place, organization, or context.
  • B. boxOfficeAdmissions
    Indicates the number of tickets sold for a film or event, reflecting how many people attended via paid admissions.
  • C. époqueDeLAction
    Indicates the historical or temporal period during which the action takes place.
  • D. The Tourist
    Indicates a relationship where an entity is characterized as a visitor or traveler temporarily present in a place rather than a permanent resident.
  • E. boxOfficeStatus chosen
    Indicates the commercial performance or financial success status of a film or media release at the box office.
  • 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_69f76e1262f48190a313318665acc189 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a196d8d881908a2f56c5722a98dd completed May 3, 2026, 7:27 p.m.
PD Predicate disambiguation batch_69f7a070e23881909a233370acb57384 completed May 3, 2026, 7:22 p.m.
Created at: May 3, 2026, 4:06 p.m.