Triple

T13196662
Position Surface form Disambiguated ID Type / Status
Subject Claudine Farrell E314128 entity
Predicate relative P37 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: [Claudine Farrell, relative, Colin Farrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colin Farrell
Context triple: [Claudine Farrell, relative, 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c626058819086f604b11af2d4eb completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d3398b08190a0fc4b6044576e0a completed May 3, 2026, 7:08 p.m.
Created at: April 9, 2026, 9:16 p.m.