Triple

T19090974
Position Surface form Disambiguated ID Type / Status
Subject The Fall (2006 film) E467279 entity
Predicate producer P490 FINISHED
Object Googly 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: Googly Films | Statement: [The Fall (2006 film), producer, Googly Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Googly Films
Context triple: [The Fall (2006 film), producer, Googly Films]
  • A. Googly Films chosen
    Googly Films is a film production company best known for producing the visually striking fantasy drama "The Fall" (2006).
  • B. See-Saw Films
    See-Saw Films is a British-Australian film and television production company known for acclaimed works such as the Academy Award–winning drama "The King’s Speech."
  • C. Tapioca Films
    Tapioca Films is a French film production company known for working on visually inventive and offbeat projects such as Jean-Pierre Jeunet’s "Micmacs à tire-larigot."
  • D. Pokeepsie Films
    Pokeepsie Films is a Spanish film production company co-founded and led by filmmaker Álex de la Iglesia, known for producing genre and independent cinema.
  • E. Echo Films
    Echo Films is a film and television production company co-founded by Jennifer Aniston, known for producing character-driven projects including the series "The Morning Show."
  • 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_69d8dd05ac4c8190b1967d8f97f3fb2f completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e34b6b348190bb868356ed8b655a completed April 20, 2026, 8:26 a.m.
Created at: April 10, 2026, 12:04 p.m.