Triple

T1181042
Position Surface form Disambiguated ID Type / Status
Subject Money Monster E25136 entity
Predicate productionCompany P490 FINISHED
Object Smokehouse Pictures E125478 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: Smokehouse Pictures | Statement: [Money Monster, productionCompany, Smokehouse Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Smokehouse Pictures
Context triple: [Money Monster, productionCompany, Smokehouse Pictures]
  • A. Smokehouse Pictures chosen
    Smokehouse Pictures is a film and television production company co-founded by George Clooney and Grant Heslov, known for producing acclaimed works such as the Oscar-winning film "Argo."
  • B. MadRiver Pictures
    MadRiver Pictures is a film production company known for financing and producing high-profile, director-driven feature films.
  • C. Thunder Road Pictures
    Thunder Road Pictures is an American film production company known for producing high-octane action movies, including the John Wick franchise.
  • D. Siren Pictures
    Siren Pictures is a South Korean television and film production company best known internationally for producing the hit Netflix series "Squid Game."
  • E. Roadside Attractions
    Roadside Attractions is an American independent film distribution company known for releasing specialty and arthouse films to theatrical audiences.
  • 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_69a494267b4c819088c97a59182bf56a completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd32c5f48190b4e2d39fa052cbb7 completed March 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f1f1c188190a96f5718c4e7d59d completed March 7, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:45 p.m.