Triple

T11009734
Position Surface form Disambiguated ID Type / Status
Subject Help! (film) E260215 entity
Predicate productionCompany P490 FINISHED
Object Proscenium Films
Proscenium Films is a film production company known for producing the 2015 Indian comedy film "Help!"
E899424 NE FINISHED

How this triple was built (4 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: Proscenium Films | Statement: [Help! (film), productionCompany, Proscenium Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Proscenium Films
Context triple: [Help! (film), productionCompany, Proscenium Films]
  • A. 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.
  • B. Praxis Films
    Praxis Films is an independent film production company best known for producing Laura Poitras’s Oscar-winning documentary "Citizenfour" about Edward Snowden and NSA surveillance.
  • C. Cinelou Films
    Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
  • D. Scion Films
    Scion Films is a British film production company known for backing acclaimed dramas such as "The Constant Gardener."
  • E. Ombra Films
    Ombra Films is a film production company known for working on action and thriller movies, including the crime thriller "Run All Night."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Proscenium Films
Triple: [Help! (film), productionCompany, Proscenium Films]
Generated description
Proscenium Films is a film production company known for producing the 2015 Indian comedy film "Help!"
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Proscenium Films
Target entity description: Proscenium Films is a film production company known for producing the 2015 Indian comedy film "Help!"
  • A. 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.
  • B. Praxis Films
    Praxis Films is an independent film production company best known for producing Laura Poitras’s Oscar-winning documentary "Citizenfour" about Edward Snowden and NSA surveillance.
  • C. Cinelou Films
    Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
  • D. Scion Films
    Scion Films is a British film production company known for backing acclaimed dramas such as "The Constant Gardener."
  • E. Ombra Films
    Ombra Films is a film production company known for working on action and thriller movies, including the crime thriller "Run All Night."
  • F. None of above. chosen

Provenance (5 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79788d44c819084f35693ed96f422 completed April 9, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69e37498b9fc8190860acede4f49ea4a completed April 18, 2026, 12:10 p.m.
NEDg Description generation batch_69e378dcc92c8190952d4acfee2a309c completed April 18, 2026, 12:28 p.m.
NED2 Entity disambiguation (via description) batch_69e37be75a588190abb9569ef1e87279 completed April 18, 2026, 12:41 p.m.
Created at: April 8, 2026, 9:25 p.m.