Triple

T10752083
Position Surface form Disambiguated ID Type / Status
Subject Nurse Betty E253594 entity
Predicate productionCompany P490 FINISHED
Object Gramercy Pictures E190391 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: Gramercy Pictures | Statement: [Nurse Betty, productionCompany, Gramercy Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gramercy Pictures
Context triple: [Nurse Betty, productionCompany, Gramercy Pictures]
  • A. Gramercy Pictures chosen
    Gramercy Pictures was an American film production and distribution company known for releasing acclaimed independent and specialty films in the 1990s.
  • B. Magnolia Pictures
    Magnolia Pictures is an American independent film distribution company known for releasing a wide range of arthouse, documentary, and foreign films.
  • C. Vistar Films
    Vistar Films is a film production company best known for its involvement in the making of the 1985 horror-comedy classic "Fright Night."
  • D. Sycamore Pictures
    Sycamore Pictures is an American film production company known for financing and producing independent and mid-budget feature films.
  • E. Benaroya Pictures
    Benaroya Pictures is an independent film production company known for financing and producing a range of critically acclaimed and commercially successful feature films.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d71dc184d0819085f8bc4edb034377 completed April 9, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbdb897f7c81909002f2478613eff8 completed April 12, 2026, 5:51 p.m.
Created at: April 8, 2026, 9:15 p.m.