Triple

T10036824
Position Surface form Disambiguated ID Type / Status
Subject Bande à part E205190 entity
Predicate productionCompany P490 FINISHED
Object Anouchka Films E752298 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: Anouchka Films | Statement: [Bande à part, productionCompany, Anouchka Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anouchka Films
Context triple: [Bande à part, productionCompany, Anouchka Films]
  • A. Anouchka Films chosen
    Anouchka Films is a film production company known for producing works such as Jean-Luc Godard’s 1967 political drama "La Chinoise."
  • B. Canana Films
    Canana Films is a Mexican film production company known for producing socially conscious and critically acclaimed Latin American cinema.
  • C. Athos Films
    Athos Films is a French film distribution company known for handling the release of notable art-house and New Wave films.
  • D. Valoria Films
    Valoria Films is a film distribution company known for handling the release of various international and independent movies.
  • E. Nala Films
    Nala Films is an independent film production company known for financing and producing critically acclaimed feature films.
  • 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdce4bb3408190ac5dae4718ef7cad completed April 2, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d28258ab088190a31ad5854d91193b completed April 5, 2026, 3:40 p.m.
Created at: March 30, 2026, 8:55 p.m.