Triple

T14455913
Position Surface form Disambiguated ID Type / Status
Subject Coco Before Chanel E358458 entity
Predicate productionCompany P490 FINISHED
Object Ciné-@
Ciné-@ is a French film production company known for backing acclaimed films such as "Coco Before Chanel."
E1102509 NE FINISHED

How this triple was built (4 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: Ciné-@ | Statement: [Coco Before Chanel, productionCompany, Ciné-@]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ciné-@
Context triple: [Coco Before Chanel, productionCompany, Ciné-@]
  • A. CinéCinéma
    CinéCinéma is a French television network and film production entity known for supporting and broadcasting a wide range of French and international cinema.
  • B. CG Cinéma
    CG Cinéma is a French film production company known for backing auteur-driven and art-house cinema.
  • C. CINE
    CINE is the London Stock Exchange ticker symbol for Cineworld Group, one of the world’s largest cinema chains.
  • D. Cinéfondation
    Cinéfondation is a Cannes Film Festival program dedicated to discovering and promoting emerging filmmakers, primarily through showcasing short and medium-length films from film schools around the world.
  • E. Cinema Rif
    Cinema Rif is a historic movie theater and cultural venue in Tangier, Morocco, known for its art-house programming and role as a hub for local and international film culture.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ciné-@
Triple: [Coco Before Chanel, productionCompany, Ciné-@]
Generated description
Ciné-@ is a French film production company known for backing acclaimed films such as "Coco Before Chanel."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ciné-@
Target entity description: Ciné-@ is a French film production company known for backing acclaimed films such as "Coco Before Chanel."
  • A. CinéCinéma
    CinéCinéma is a French television network and film production entity known for supporting and broadcasting a wide range of French and international cinema.
  • B. CG Cinéma
    CG Cinéma is a French film production company known for backing auteur-driven and art-house cinema.
  • C. CINE
    CINE is the London Stock Exchange ticker symbol for Cineworld Group, one of the world’s largest cinema chains.
  • D. Cinéfondation
    Cinéfondation is a Cannes Film Festival program dedicated to discovering and promoting emerging filmmakers, primarily through showcasing short and medium-length films from film schools around the world.
  • E. Cinema Rif
    Cinema Rif is a historic movie theater and cultural venue in Tangier, Morocco, known for its art-house programming and role as a hub for local and international film culture.
  • F. None of above. chosen

Provenance (5 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91a9c0d48190ae015e5e0db806ca completed April 14, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d86dbc0819085fef8fa8b45b373 completed May 8, 2026, 4:58 a.m.
NEDg Description generation batch_69fd6efed3108190a524c64adf740303 completed May 8, 2026, 5:05 a.m.
NED2 Entity disambiguation (via description) batch_69fd6f8648408190aed910a7f269abee completed May 8, 2026, 5:07 a.m.
Created at: April 10, 2026, 1:19 a.m.