Triple

T4579286
Position Surface form Disambiguated ID Type / Status
Subject Snowden (2016 film) E101813 entity
Predicate productionCompany P490 FINISHED
Object Wild Bunch E322415 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: Wild Bunch | Statement: [Snowden (2016 film), productionCompany, Wild Bunch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wild Bunch
Context triple: [Snowden (2016 film), productionCompany, Wild Bunch]
  • A. Wild Bunch chosen
    Wild Bunch is a European film production and distribution company known for backing a wide range of acclaimed international and independent films.
  • B. Outlaw Productions
    Outlaw Productions is a film and television production company known for producing a range of Hollywood genre movies and commercial features.
  • C. Rhino Films
    Rhino Films is an independent film production company known for backing distinctive and often offbeat projects, including the cult classic adaptation of "Fear and Loathing in Las Vegas."
  • D. Zabivaka
    Zabivaka is the wolf character that served as the official mascot for major international football tournaments hosted by Russia, including the 2018 FIFA World Cup.
  • E. Rumble Films
    Rumble Films is an American film production company known for producing independent and genre-driven movies.
  • 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_69bd43d4ce208190b53158c882b222e3 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd58e3e028819083c4662deb9f3c03 completed March 20, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3f532dc81909b6c464defada832 completed March 20, 2026, 11:10 p.m.
Created at: March 20, 2026, 1:10 p.m.