Triple

T20995353
Position Surface form Disambiguated ID Type / Status
Subject Flesh and Bone E517133 entity
Predicate cinematography P1953 FINISHED
Object Philippe Rousselot 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: Philippe Rousselot | Statement: [Flesh and Bone, cinematography, Philippe Rousselot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philippe Rousselot
Context triple: [Flesh and Bone, cinematography, Philippe Rousselot]
  • A. Philippe Rousselot chosen
    Philippe Rousselot is an acclaimed French cinematographer known for his visually distinctive work on numerous major films across several decades.
  • B. Philippe Sueur
    Philippe Sueur is a French politician best known for serving as the long-time mayor of the spa town Enghien-les-Bains in the Île-de-France region.
  • C. Bruno Coulais
    Bruno Coulais is a French composer best known for his atmospheric and innovative film scores, particularly in European cinema and animation.
  • D. Ludovic Rohart
    Ludovic Rohart is a French local politician serving as the mayor of the northern commune of Orchies.
  • E. Philippe Kirsch
    Philippe Kirsch is a Canadian jurist and diplomat who served as the inaugural president of the International Criminal Court and played a key role in its founding.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5006e2881909fc2383f841740cc completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc1fd5d48190a56981cee95ebd69 completed April 21, 2026, 4:25 a.m.
Created at: April 16, 2026, 1:50 p.m.