Triple

T4389851
Position Surface form Disambiguated ID Type / Status
Subject Crome Yellow E99335 entity
Predicate protagonist P268 FINISHED
Object Denis Stone E435929 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: Denis Stone | Statement: [Crome Yellow, protagonist, Denis Stone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denis Stone
Context triple: [Crome Yellow, protagonist, 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. Robert Baer
    Robert Baer is a former CIA case officer and author known for his memoirs on Middle East espionage and U.S. intelligence, one of which inspired the film "Syriana."
  • 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_69b3454f739481909ff6c28331f0c0b9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35282cb2c8190856da20bb87e88ff completed March 12, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5f5ec77d081909b07ebd004be136f completed March 14, 2026, 11:57 p.m.
Created at: March 12, 2026, 11:19 p.m.