Triple

T18000979
Position Surface form Disambiguated ID Type / Status
Subject Trudie Styler E430623 entity
Predicate founded P104 FINISHED
Object Xingu Films NE NERFINISHED

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: Xingu Films | Statement: [Trudie Styler, founded, Xingu Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xingu Films
Context triple: [Trudie Styler, founded, Xingu Films]
  • A. Xingu Films chosen
    Xingu Films is a film production company known for producing independent and art-house cinema, including the movie "Moon."
  • B. Cinelou Films
    Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
  • C. Valoria Films
    Valoria Films is a film distribution company known for handling the release of various international and independent movies.
  • D. Aquarius Films
    Aquarius Films is an Australian film and television production company known for creating distinctive, character-driven screen content for both local and international audiences.
  • E. Eldorado Films
    Eldorado Films is a film production company best known for its involvement in the 1984 adventure romantic comedy "Romancing the Stone."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b3e82ca48190aeb53e03c95ef223 completed April 19, 2026, 10:52 a.m.
Created at: April 10, 2026, 10:23 a.m.