Triple

T5531747
Position Surface form Disambiguated ID Type / Status
Subject Made in Dagenham E145064 entity
Predicate productionCompany P490 FINISHED
Object Number 9 Films E257835 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: Number 9 Films | Statement: [Made in Dagenham, productionCompany, Number 9 Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Number 9 Films
Context triple: [Made in Dagenham, productionCompany, Number 9 Films]
  • A. Number 9 Films chosen
    Number 9 Films is a British film production company known for producing acclaimed independent and arthouse films.
  • B. Imagine Films
    Imagine Films is a film production division associated with the American entertainment company Imagine Entertainment, known for developing and producing motion pictures.
  • C. Element Films
    Element Films is a film production company known for working on acclaimed independent and politically themed cinema such as Ken Loach’s "The Wind That Shakes the Barley."
  • D. Dendy Films
    Dendy Films is an Australian film distribution company known for releasing independent, arthouse, and international cinema.
  • E. Diaphana Films
    Diaphana Films is a French film distribution and production company known for handling acclaimed international and auteur cinema.
  • 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_69c008f9955881909bfa8348b56b4739 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f9d17ec8190b93b12931a4c1b33 completed March 22, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c028094fa48190a1f48779a7963af9 completed March 22, 2026, 5:34 p.m.
Created at: March 22, 2026, 3:34 p.m.