Triple

T15019987
Position Surface form Disambiguated ID Type / Status
Subject Anomalisa E378057 entity
Predicate voiceActor P1507 FINISHED
Object David Thewlis E198561 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: David Thewlis | Statement: [Anomalisa, voiceActor, David Thewlis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Thewlis
Context triple: [Anomalisa, voiceActor, David Thewlis]
  • A. David Thewlis chosen
    David Thewlis is an English actor and filmmaker best known for roles such as Remus Lupin in the Harry Potter film series and his award-winning performance in Mike Leigh’s "Naked."
  • B. Joseph Fiennes
    Joseph Fiennes is an English actor known for his roles in films such as "Shakespeare in Love" and various historical and dramatic productions in both cinema and television.
  • C. Peter Firth
    Peter Firth is an English actor best known for his roles in the film "Equus" and the television series "Spooks" (MI-5).
  • D. Jonathan Rhys Hill
    Jonathan Rhys Hill is a composer best known for his work on television drama scores, including the series "The Trial of Christine Keeler."
  • E. Daniel Mays
    Daniel Mays is a British actor known for his versatile character roles in film and television, including prominent performances in projects like "Line of Duty," "Ashes to Ashes," and "Rogue One: A Star Wars Story."
  • 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_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded76445988190984b57de66e00c4a completed April 15, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f24967c8190b0bdb84b88a0aaa3 completed May 9, 2026, 4:21 p.m.
Created at: April 10, 2026, 2:56 a.m.