Triple

T16683830
Position Surface form Disambiguated ID Type / Status
Subject Marty Faranan E405406 entity
Predicate portrayedBy P1507 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: [Marty Faranan, portrayedBy, Colin Farrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colin Farrell
Context triple: [Marty Faranan, portrayedBy, 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37d70d3f8819087d1bd700c94a83f completed April 18, 2026, 12:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d32e7b48190b7dd4660bed4789d completed May 10, 2026, 2:58 p.m.
Created at: April 10, 2026, 5:19 a.m.