Triple

T22891091
Position Surface form Disambiguated ID Type / Status
Subject Epic (2013 film) E568040 entity
Predicate voiceActor P1507 FINISHED
Object Colin Farrell NE NERFINISHED

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: Colin Farrell | Statement: [Epic (2013 film), voiceActor, Colin Farrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colin Farrell
Context triple: [Epic (2013 film), voiceActor, Colin Farrell]
  • A. Colin Farrell chosen
    Colin Farrell is an Irish actor known for his versatile performances in films such as "In Bruges," "Phone Booth," and "The Banshees of Inisherin."
  • B. Nicholas Farrell
    Nicholas Farrell is a British actor known for his work in film, television, and theatre, including prominent roles in productions such as Kenneth Branagh’s "Hamlet" and the historical drama "Chariots of Fire."
  • C. Brendan Gleeson
    Brendan Gleeson is an acclaimed Irish actor known for his powerful character roles in films such as In Bruges, The Guard, and the Harry Potter series.
  • D. Seamus Tierney
    Seamus Tierney is a cinematographer known for his work on the film "Love, Antosha."
  • E. Kevin Meaney
    Kevin Meaney was an American stand-up comedian and actor known for his offbeat, family-themed humor and appearances on shows like "The Tonight Show" and the sitcom "Uncle Buck."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458c23ec81908fa2570692c6614f completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f17fc59e108190a22f90c2439830fb completed April 29, 2026, 3:49 a.m.
Created at: April 17, 2026, 3:40 p.m.