Triple

T5706099
Position Surface form Disambiguated ID Type / Status
Subject Practical Magic E125786 entity
Predicate productionCompany P490 FINISHED
Object Di Novi Pictures E127059 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: Di Novi Pictures | Statement: [Practical Magic, productionCompany, Di Novi Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Di Novi Pictures
Context triple: [Practical Magic, productionCompany, Di Novi Pictures]
  • A. Di Novi Pictures chosen
    Di Novi Pictures is an American film production company founded by producer Denise Di Novi, known for its work on character-driven dramas and literary adaptations.
  • B. Vistar Films
    Vistar Films is a film production company best known for its involvement in the making of the 1985 horror-comedy classic "Fright Night."
  • C. Diaphana Films
    Diaphana Films is a French film distribution and production company known for handling acclaimed international and auteur cinema.
  • D. Overture Films
    Overture Films was an American independent film production and distribution company active in the late 2000s, known for releasing a range of mid-budget and specialty films.
  • E. Benaroya Pictures
    Benaroya Pictures is an independent film production company known for financing and producing a range of critically acclaimed and commercially successful 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02459cd18819080fda0b481d11f08 completed March 22, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a666d788190a0f786d12391a44b completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:45 p.m.