Triple

T15441322
Position Surface form Disambiguated ID Type / Status
Subject John Birt in Frost/Nixon E369906 entity
Predicate portrayedBy P1507 FINISHED
Object Matthew Macfadyen E75520 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: Matthew Macfadyen | Statement: [John Birt in Frost/Nixon, portrayedBy, Matthew Macfadyen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Macfadyen
Context triple: [John Birt in Frost/Nixon, portrayedBy, Matthew Macfadyen]
  • A. Matthew Macfadyen chosen
    Matthew Macfadyen is an English actor known for his versatile performances in film and television, including prominent roles in "Pride & Prejudice," "Succession," and various British dramas.
  • B. Mattias Ferrell
    Mattias Ferrell is one of the sons of American actor and comedian Will Ferrell.
  • C. Seth Gabel
    Seth Gabel is an American actor known for his roles in television series such as "Fringe," "Salem," and "Nip/Tuck."
  • D. Zach Woods
    Zach Woods is an American actor and comedian best known for his roles on television series such as "The Office," "Silicon Valley," and "Avenue 5."
  • E. Max Greenfield
    Max Greenfield is an American actor best known for his role as Schmidt on the television sitcom "New Girl."
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef55f5c8190a32b1b6ad1daf454 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c3293dc819097f9e56963c333ee completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 3:21 a.m.