Triple

T19328482
Position Surface form Disambiguated ID Type / Status
Subject Death Comes to Pemberley E483421 entity
Predicate director P255 FINISHED
Object Daniel Percival NE NERFINISHED

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: Daniel Percival | Statement: [Death Comes to Pemberley, director, Daniel Percival]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Percival
Context triple: [Death Comes to Pemberley, director, Daniel Percival]
  • A. Daniel Percival chosen
    Daniel Percival is a British television director and producer known for his work on high-profile drama series, including serving as an executive producer on "The Man in the High Castle."
  • B. Brian Percival
    Brian Percival is a British film and television director best known for his work on the historical drama series "Downton Abbey" and various acclaimed period pieces.
  • C. Brian Ruckley
    Brian Ruckley is a Scottish fantasy and comic book writer best known in comics for scripting IDW Publishing’s main Transformers series.
  • D. Anthony Peckham
    Anthony Peckham is a South African–born screenwriter best known for scripting films such as "Invictus" and "Sherlock Holmes."
  • E. Michael Buckland
    Michael Buckland is an American information scientist and librarian known for his influential work on information retrieval, library services, and the theory of information systems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e6163f32f48190be17cccf4e537372 completed April 20, 2026, 12:04 p.m.
Created at: April 10, 2026, 1:33 p.m.