Triple

T10285572
Position Surface form Disambiguated ID Type / Status
Subject Wilkes E241217 entity
Predicate hasNotableBearer P458 FINISHED
Object John Wilkes E107833 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: John Wilkes | Statement: [Wilkes, hasNotableBearer, John Wilkes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Wilkes
Context triple: [Wilkes, hasNotableBearer, John Wilkes]
  • A. John Wilkes chosen
    John Wilkes was an 18th-century English radical politician, journalist, and champion of civil liberties who became a symbol of the fight for parliamentary reform.
  • B. John Rockingham
    John Rockingham was an Australian Army officer best known for leading Commonwealth forces with distinction during the Korean War, particularly in the Battle of Kapyong.
  • C. Thomas Tickell
    Thomas Tickell was an early 18th-century English poet and translator associated with Joseph Addison and the Whig literary circle.
  • D. William Duane
    William Duane was an influential early American journalist and editor of the Philadelphia Aurora, known for his staunch support of Jeffersonian Republican politics.
  • E. James Widdoes
    James Widdoes is an American actor, director, and television producer best known for directing and producing numerous sitcoms, including extensive work on series like Two and a Half Men and Mom.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2b737788190bfadd0d48ad38f5b completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f8444c48819095100c6d1d45ccc7 completed April 9, 2026, 12:52 a.m.
Created at: April 6, 2026, 11:40 a.m.