Triple

T9937319
Position Surface form Disambiguated ID Type / Status
Subject In the Land of Blood and Honey E193989 entity
Predicate productionCompany P490 FINISHED
Object GK Films E130832 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: GK Films | Statement: [In the Land of Blood and Honey, productionCompany, GK Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GK Films
Context triple: [In the Land of Blood and Honey, productionCompany, GK Films]
  • A. GK Films chosen
    GK Films is a British-American production company founded by producer Graham King, known for backing acclaimed films such as Argo, The Departed, and Bohemian Rhapsody.
  • 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. Misher Films
    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."
  • D. GV Films
    GV Films is an Indian film production and distribution company known for backing several notable Tamil and South Indian movies.
  • E. SKA Films
    SKA Films is a British film production company co-founded by director Matthew Vaughn, known for producing stylish crime and action movies such as "Layer Cake."
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5e4e19881909879b394090d6629 completed April 2, 2026, 12:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69d228f259b081909ce8a90ec1adad0d completed April 5, 2026, 9:18 a.m.
Created at: March 30, 2026, 8:44 p.m.