Triple

T6804609
Position Surface form Disambiguated ID Type / Status
Subject Jack Davenport E156271 entity
Predicate relative P37 FINISHED
Object Jonathan Aitken
Jonathan Aitken is a British former Conservative politician and cabinet minister who became widely known for his high-profile perjury conviction in the late 1990s.
 E643959 NE FINISHED

How this triple was built (4 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: Jonathan Aitken | Statement: [Jack Davenport, relative, Jonathan Aitken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jonathan Aitken
Context triple: [Jack Davenport, relative, Jonathan Aitken]
  • A. Richard Hiscott
    Richard Hiscott is an editor known for his work on the television series "Willow."
  • B. Andrew MacRitchie
    Andrew MacRitchie is a film editor known for his work on major feature films, including the James Bond movie "Die Another Day."
  • C. David Farquharson
    David Farquharson was an architect known for designing South Hall.
  • D. Kenneth Muir
    Kenneth Muir was a prominent British literary scholar and Shakespearean critic known for his influential editions and analyses of Elizabethan and Jacobean drama.
  • E. Harry Aitken
    Harry Aitken was an early American film producer and studio executive best known for backing landmark and controversial silent-era epics such as D. W. Griffith’s "The Birth of a Nation."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jonathan Aitken
Triple: [Jack Davenport, relative, Jonathan Aitken]
Generated description
Jonathan Aitken is a British former Conservative politician and cabinet minister who became widely known for his high-profile perjury conviction in the late 1990s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jonathan Aitken
Target entity description: Jonathan Aitken is a British former Conservative politician and cabinet minister who became widely known for his high-profile perjury conviction in the late 1990s.
  • A. Richard Hiscott
    Richard Hiscott is an editor known for his work on the television series "Willow."
  • B. Andrew MacRitchie
    Andrew MacRitchie is a film editor known for his work on major feature films, including the James Bond movie "Die Another Day."
  • C. David Farquharson
    David Farquharson was an architect known for designing South Hall.
  • D. Kenneth Muir
    Kenneth Muir was a prominent British literary scholar and Shakespearean critic known for his influential editions and analyses of Elizabethan and Jacobean drama.
  • E. Harry Aitken
    Harry Aitken was an early American film producer and studio executive best known for backing landmark and controversial silent-era epics such as D. W. Griffith’s "The Birth of a Nation."
  • F. None of above. chosen

Provenance (5 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_69c68826e6a48190a3d220b541e639de completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2ea459c819095388218d53c250a completed March 27, 2026, 6:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a309dd4c81909f2a652f211911bc completed March 28, 2026, 9:44 a.m.
NEDg Description generation batch_69c7a46d95b88190bbadf3e8d1788489 completed March 28, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_69c7a52e6a1c8190bf45e0aa7a920baf completed March 28, 2026, 9:53 a.m.
Created at: March 27, 2026, 2:16 p.m.