Triple

T31031595
Position Surface form Disambiguated ID Type / Status
Subject Pénélope E790741 entity
Predicate hasWorkCinematographer P90619 FINISHED
Object Jean-Jacques Tarbès 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: Jean-Jacques Tarbès | Statement: [Pénélope, hasWorkCinematographer, Jean-Jacques Tarbès]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasWorkCinematographer
Context triple: [Pénélope, hasWorkCinematographer, Jean-Jacques Tarbès]
  • A. cinematographerOfWork chosen
    Indicates that a person served as the cinematographer (director of photography) for a specific creative work.
  • B. workedBehindTheCameraAs
    Indicates that a person contributed to a production in an off-screen or non-acting role, such as directing, producing, or other behind-the-scenes work.
  • C. hasCameraWork
    Indicates that an entity features or involves specific camera operation or cinematographic techniques performed by another entity.
  • D. hasWorkedOnFilmBy
    Indicates that one entity has worked on a film that was created, directed, or otherwise authored by another entity.
  • E. frequentCinematographerCollaborator
    Indicates a relationship where a cinematographer regularly works with or repeatedly collaborates on projects with the same director or creative partner.
  • 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_69f224c97a788190b5da1ead6038a74e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69fd509e6bc08190b263923c2f40fea3 completed May 8, 2026, 2:55 a.m.
PD Predicate disambiguation batch_69fd4fd1a58881909d4b84de1b24e380 completed May 8, 2026, 2:52 a.m.
Created at: April 29, 2026, 8:59 p.m.