Triple

T6334125
Position Surface form Disambiguated ID Type / Status
Subject David Gyasi E142449 entity
Predicate name P16 FINISHED
Object David Gyasi E142449 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: David Gyasi | Statement: [David Gyasi, name, David Gyasi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Gyasi
Context triple: [David Gyasi, name, David Gyasi]
  • A. David Gyasi chosen
    David Gyasi is a British actor known for his roles in films like "Interstellar" and series such as "Troy: Fall of a City" and "Carnival Row."
  • B. Darius Ogden Mills
    Darius Ogden Mills was a prominent 19th-century American banker, financier, and philanthropist influential in the development of California.
  • C. Daniel Lyons
    Daniel Lyons is a fictional character from the British television drama series "Years and Years," portrayed by actor Russell Tovey.
  • D. David Gianotten
    David Gianotten is a Dutch architect and managing partner at the renowned architecture firm OMA, known for leading major international projects and the firm’s overall direction.
  • E. Alex Gorsky
    Alex Gorsky is an American business executive best known for serving as chairman and CEO of Johnson & Johnson.
  • 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06549084c8190b73fd94c9e0cb302 completed March 22, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c60424a5dc8190820970fce13776ac completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.