Triple

T18343663
Position Surface form Disambiguated ID Type / Status
Subject Henry Wimbush E439474 entity
Predicate appearsAlongside P25756 FINISHED
Object Denis Stone 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: Denis Stone | Statement: [Henry Wimbush, appearsAlongside, Denis Stone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denis Stone
Context triple: [Henry Wimbush, appearsAlongside, Denis Stone]
  • A. Denis Stone chosen
    Denis Stone is the introspective, somewhat naive young poet who serves as the protagonist and observer of the social satire in Aldous Huxley’s novel "Crome Yellow."
  • B. Ken Ledeen
    Ken Ledeen is a technology entrepreneur and author best known for co-writing influential works on digital technology and its societal impact.
  • C. Peter Kornbluh
    Peter Kornbluh is an American historian and investigative journalist known for his work on U.S. foreign policy and declassified government documents, particularly regarding Latin America.
  • D. Christopher Nourse
    Christopher Nourse is a British arts administrator and producer known for his leadership roles in major dance and performing arts organizations.
  • E. Tim Weiner
    Tim Weiner is an American journalist and author best known for his Pulitzer Prize-winning reporting and his books on the history of U.S. intelligence agencies.
  • 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_69d8b9175fec8190af865699b4e64d8c completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e514f2c8ec8190b045482846a68204 completed April 19, 2026, 5:46 p.m.
Created at: April 10, 2026, 10:37 a.m.