Triple

T13687022
Position Surface form Disambiguated ID Type / Status
Subject Exam E328157 entity
Predicate distributor P1951 FINISHED
Object Independent Film Company E952470 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: Independent Film Company | Statement: [Exam, distributor, Independent Film Company]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Independent Film Company
Context triple: [Exam, distributor, Independent Film Company]
  • A. Independent Film Company chosen
    Independent Film Company is a British production and sales company known for financing and distributing independent feature films.
  • B. Big Indie Pictures
    Big Indie Pictures is a film production company known for backing independent and character-driven movies such as the comedy-drama "Troop Zero."
  • C. Integral Films
    Integral Films is a film production company known for working on projects such as David Cronenberg’s satirical drama "Maps to the Stars."
  • D. Arthouse Entertainment
    Arthouse Entertainment is a music publishing and production company known for developing and representing hit songwriters and producers across mainstream pop and other genres.
  • E. Intermedia Films
    Intermedia Films is an independent film production company known for financing and producing a range of international 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc670968881908e2b4fdf656c7285 completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944981ec8190be5ff39b7c2c70ab completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.