Triple

T13310259
Position Surface form Disambiguated ID Type / Status
Subject La Marche de l'empereur E317041 entity
Predicate productionCompany P490 FINISHED
Object Bonne Pioche E317047 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: Bonne Pioche | Statement: [La Marche de l'empereur, productionCompany, Bonne Pioche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bonne Pioche
Context triple: [La Marche de l'empereur, productionCompany, Bonne Pioche]
  • A. Bonne Pioche chosen
    Bonne Pioche is a French film and television production company known internationally for producing acclaimed documentaries such as "March of the Penguins."
  • B. Chapotel
    Chapotel is a French surname associated with individuals such as Rose Chapotel.
  • C. La Sablonière
    La Sablonière is one of the small islets within the Les Écréhous reef and island group off the coast of Jersey in the Channel Islands.
  • D. Le Tote
    Le Tote is a fashion rental subscription service company that expanded into traditional retail by acquiring the historic department store chain Lord & Taylor.
  • E. Le Bonheur
    Le Bonheur is a philosophical poetry collection by French poet and Nobel laureate Sully Prudhomme that meditates on the nature and pursuit of human happiness.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f56abc8190951774a999e2ce11 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e7b9a48190a33b04df8ad45ed8 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:29 p.m.