Triple

T7436203
Position Surface form Disambiguated ID Type / Status
Subject The Bear E171621 entity
Predicate cinematographyBy P1953 FINISHED
Object Philippe Rousselot E213637 NE 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: Philippe Rousselot | Statement: [The Bear, cinematographyBy, Philippe Rousselot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philippe Rousselot
Context triple: [The Bear, cinematographyBy, 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. Bruno Coulais
    Bruno Coulais is a French composer best known for his atmospheric and innovative film scores, particularly in European cinema and animation.
  • C. 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.
  • D. Philippe Soupault
    Philippe Soupault was a French writer and poet who co-founded the Surrealist movement and played a crucial role in developing early 20th-century avant-garde literature.
  • E. Michel Andrault
    Michel Andrault was a prominent French architect known for his influential large-scale housing and urban development projects in the late 20th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c68a64228c8190affaec2a8127ce7b completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f347f25081908e6086d4073295f5 completed March 27, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c93fa2550481908348b8b4dd23d6df completed March 29, 2026, 3:05 p.m.
Created at: March 27, 2026, 3:13 p.m.