Triple

T22767240
Position Surface form Disambiguated ID Type / Status
Subject Betsy’s Wedding E563158 entity
Predicate cinematographyBy P1953 FINISHED
Object Kelvin Pike 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: Kelvin Pike | Statement: [Betsy’s Wedding, cinematographyBy, Kelvin Pike]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kelvin Pike
Context triple: [Betsy’s Wedding, cinematographyBy, Kelvin Pike]
  • A. Kelvin Pike chosen
    Kelvin Pike was a British cinematographer known for his work on notable films including "The Dresser."
  • B. Joseph Kipness
    Joseph Kipness was a theatrical producer best known for his work on Broadway musicals such as "Applause."
  • C. Paul Kernaghan
    Paul Kernaghan is a British public official and former senior police officer who has served as the House of Lords Commissioner for Standards, overseeing investigations into members’ conduct.
  • D. Douglas Pike
    Douglas Pike was a prominent American diplomat and scholar known for his influential analyses of the Viet Cong and the Vietnam War.
  • E. Joseph Pike
    Joseph Pike is a relatively obscure individual whose name is notably associated with the surname Pike but who lacks widely recognized public prominence or distinguishing achievements in major historical or cultural records.
  • 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_69e24552e11c81909c2d61578a558bd7 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17a81d3348190b005a43a5e03d406 completed April 29, 2026, 3:26 a.m.
Created at: April 17, 2026, 3:27 p.m.