Triple

T23061656
Position Surface form Disambiguated ID Type / Status
Subject The Measure of a Man E574917 entity
Predicate distributedBy P1951 FINISHED
Object Diaphana Films NE NERFINISHED

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: Diaphana Films | Statement: [The Measure of a Man, distributedBy, Diaphana Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diaphana Films
Context triple: [The Measure of a Man, distributedBy, Diaphana Films]
  • A. Diaphana Films chosen
    Diaphana Films is a French film distribution and production company known for handling acclaimed international and auteur cinema.
  • B. Cinelou Films
    Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
  • C. Valoria Films
    Valoria Films is a film distribution company known for handling the release of various international and independent movies.
  • D. Cineyug Films
    Cineyug Films is an Indian film production company known for backing major Bollywood projects and entertainment ventures.
  • E. Aquarius Films
    Aquarius Films is an Australian film and television production company known for creating distinctive, character-driven screen content for both local and international audiences.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245bd6e4c8190bb8942245b68cad5 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1899ff96081908d89a07a3b1065c8 completed April 29, 2026, 4:31 a.m.
Created at: April 17, 2026, 3:55 p.m.