Triple

T15289314
Position Surface form Disambiguated ID Type / Status
Subject Richard Jewell (film) E365484 entity
Predicate productionCompany P490 FINISHED
Object Misher Films E257912 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: Misher Films | Statement: [Richard Jewell (film), productionCompany, Misher Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Misher Films
Context triple: [Richard Jewell (film), productionCompany, Misher Films]
  • A. Misher Films chosen
    Misher Films is an American film production company known for producing a range of mainstream Hollywood movies, including the biographical sports comedy-drama "Fighting with My Family."
  • B. Muktha Films
    Muktha Films is an Indian film production company best known for producing acclaimed Tamil cinema, including the classic crime drama "Nayakan."
  • C. Cinelou Films
    Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
  • D. Nala Films
    Nala Films is an independent film production company known for financing and producing critically acclaimed feature films.
  • E. Sahai Films
    Sahai Films is an Indian film production company known for producing the cult classic television film "In Which Annie Gives It Those Ones."
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00e5635b4819092a69b5806d15bff completed April 15, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69feef7d4da4819080f101c3a525ea11 completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:15 a.m.