Triple

T8317503
Position Surface form Disambiguated ID Type / Status
Subject Battle of the Sexes E194742 entity
Predicate productionCompany P490 FINISHED
Object Decibel Films E200831 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: Decibel Films | Statement: [Battle of the Sexes, productionCompany, Decibel Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Decibel Films
Context triple: [Battle of the Sexes, productionCompany, Decibel Films]
  • A. Decibel Films chosen
    Decibel Films is a British film production company associated with producer Christian Colson, known for developing and producing feature films.
  • B. Decibel Films
    Decibel Films is a film production company known for producing the 2018 thriller "Yesterday."
  • C. TDE Films
    TDE Films is the film and visual media division of the hip-hop record label Top Dawg Entertainment, focused on producing video and cinematic content tied to the label’s artists and brand.
  • D. Dimension Films
    Dimension Films is an American film production and distribution company best known for releasing popular horror and genre franchises such as Scream and Scary Movie.
  • E. Diaphana Films
    Diaphana Films is a French film distribution and production company known for handling acclaimed international and auteur cinema.
  • 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_69ca82e6e2648190a31eaf6f4f757b2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f630ea881909fb639383e60aee9 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd958cf0808190af59e36c35b91e58 completed April 1, 2026, 10 p.m.
Created at: March 30, 2026, 5:55 p.m.