Triple

T8770922
Position Surface form Disambiguated ID Type / Status
Subject Drew Barrymore E208457 entity
Predicate founded P104 FINISHED
Object Flower Films E512523 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: Flower Films | Statement: [Drew Barrymore, founded, Flower Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flower Films
Context triple: [Drew Barrymore, founded, Flower Films]
  • A. Flower Films chosen
    Flower Films is an American film and television production company co-founded by actress Drew Barrymore, known for producing a range of popular romantic comedies and dramas.
  • B. Blossom Films
    Blossom Films is a film and television production company founded by actress Nicole Kidman, known for developing high-profile, character-driven projects.
  • 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. Diaphana Films
    Diaphana Films is a French film distribution and production company known for handling acclaimed international and auteur cinema.
  • E. Ruby Films
    Ruby Films is a British film and television production company known for producing high-quality period dramas and literary adaptations.
  • 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_69ca835edb4481909b4aafb616dc5eb7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f2b08f881909f3d4fab2eda1d67 completed March 31, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51b7d05c8190b84e02a8796d3422 completed April 3, 2026, 5:35 a.m.
Created at: March 30, 2026, 6:41 p.m.