Triple

T10367487
Position Surface form Disambiguated ID Type / Status
Subject Heartbreaker E244292 entity
Predicate cinematographer P1953 FINISHED
Object Thierry Arbogast E398585 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: Thierry Arbogast | Statement: [Heartbreaker, cinematographer, Thierry Arbogast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thierry Arbogast
Context triple: [Heartbreaker, cinematographer, Thierry Arbogast]
  • A. Thierry Arbogast chosen
    Thierry Arbogast is a French cinematographer renowned for his long-standing collaboration with director Luc Besson on visually distinctive films.
  • B. Thierry Burkhard
    Thierry Burkhard is a French Army general who has served as France’s top military officer and a key figure in shaping the country’s contemporary defense policy and armed forces.
  • C. Didier Aldigier
    Didier Aldigier is a French local politician serving as the mayor of the commune of Pont-de-l’Isère in southeastern France.
  • D. Luc Teyssier
    Luc Teyssier is a charming, roguish French thief who becomes the romantic lead opposite Meg Ryan’s character in the 1995 romantic comedy film "French Kiss."
  • E. Patrick Baudry
    Patrick Baudry is a French astronaut and test pilot who became one of the first French citizens to fly in space.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e96fd6f081908f630a16106996d9 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbac97ce2481908ea11d6290a9bf2f completed April 12, 2026, 2:30 p.m.
Created at: April 6, 2026, noon