Triple

T12768645
Position Surface form Disambiguated ID Type / Status
Subject Great Expectations (2012 film) E305188 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: [Great Expectations (2012 film), productionCompany, Number 9 Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Number 9 Films
Context triple: [Great Expectations (2012 film), 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. Nyerai Films
    Nyerai Films is a Zimbabwean film production company known for creating socially conscious, women-centered stories under the leadership of writer and filmmaker Tsitsi Dangarembga.
  • C. Riama Film
    Riama Film is an Italian film production company best known for producing Federico Fellini’s classic 1960 drama "La Dolce Vita."
  • D. Imagine Films
    Imagine Films is a film production division associated with the American entertainment company Imagine Entertainment, known for developing and producing motion pictures.
  • E. Dohafilms
    Dohafilms is a film production company known for helping produce the 2014 animated adaptation of Kahlil Gibran’s "The Prophet."
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df3b2f88190b37b696400178795 completed April 10, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684f750a08190abf6122baa579bc4 completed May 2, 2026, 11:12 p.m.
Created at: April 9, 2026, 5:28 p.m.