Triple

T23464253
Position Surface form Disambiguated ID Type / Status
Subject Boltzmann Medal E569061 entity
Predicate hasRecipient P108 FINISHED
Object John Cardy 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: John Cardy | Statement: [Boltzmann Medal, hasRecipient, John Cardy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Cardy
Context triple: [Boltzmann Medal, hasRecipient, John Cardy]
  • A. John Cardy chosen
    John Cardy is a British theoretical physicist renowned for his influential work in statistical mechanics and conformal field theory.
  • B. Stuart Card
    Stuart Card is a pioneering researcher in human-computer interaction and cognitive psychology, known for foundational work on user interface design and models of human performance with computers.
  • C. Garth Fisher
    Garth Fisher is a prominent American plastic surgeon best known for his appearances on the reality TV show "Extreme Makeover."
  • D. Daren Ackwood
    Daren Ackwood is a fictional character portrayed by actor Daren Kagasoff, likely in a television or film production.
  • E. James Card
    James Card was an influential American film archivist and curator, best known for his pioneering work in film preservation and his role in inspiring major film culture institutions such as the Telluride Film Festival.
  • 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_69e2458ebd808190b3298163132cfb0b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a69f0a54819084c19c248a572253 completed April 29, 2026, 6:35 a.m.
Created at: April 17, 2026, 5:54 p.m.