Triple

T15296345
Position Surface form Disambiguated ID Type / Status
Subject Phone Booth (film score) E365666 entity
Predicate associatedWithActor P2830 FINISHED
Object Colin Farrell E78591 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: Colin Farrell | Statement: [Phone Booth (film score), associatedWithActor, Colin Farrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colin Farrell
Context triple: [Phone Booth (film score), associatedWithActor, 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. Denis O'Hare
    Denis O'Hare is an American actor known for his versatile character roles in film, television, and theater, including prominent appearances in "American Horror Story" and "True Blood."
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e036848c1881908fbaaae0216d6d27 completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01e2a03c81909ab24d4ed2b54698 completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:15 a.m.