Triple

T19447859
Position Surface form Disambiguated ID Type / Status
Subject Squid Game episode 7 E486528 entity
Predicate productionCompany P490 FINISHED
Object Sirens Pictures 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: Sirens Pictures | Statement: [Squid Game episode 7, productionCompany, Sirens Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sirens Pictures
Context triple: [Squid Game episode 7, productionCompany, Sirens Pictures]
  • A. Siren Pictures chosen
    Siren Pictures is a South Korean television and film production company best known internationally for producing the hit Netflix series "Squid Game."
  • B. Sycamore Pictures
    Sycamore Pictures is an American film production company known for financing and producing independent and mid-budget feature films.
  • C. Sister Pictures
    Sister Pictures is a British television production company known for creating high-profile, critically acclaimed drama series.
  • D. MadRiver Pictures
    MadRiver Pictures is a film production company known for financing and producing high-profile, director-driven feature films.
  • E. Overture Films
    Overture Films was an American independent film production and distribution company active in the late 2000s, known for releasing a range of mid-budget and specialty films.
  • 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6338b25d88190bc137a411576c73f completed April 20, 2026, 2:09 p.m.
Created at: April 10, 2026, 1:38 p.m.