Triple

T598045
Position Surface form Disambiguated ID Type / Status
Subject John Boyega E11429 entity
Predicate name P16 FINISHED
Object John Boyega E11429 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: John Boyega | Statement: [John Boyega, name, John Boyega]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Boyega
Context triple: [John Boyega, name, John Boyega]
  • A. John Boyega chosen
    John Boyega is a British actor and producer best known for his role as Finn in the Star Wars sequel trilogy.
  • B. Pedro Pascal
    Pedro Pascal is a Chilean-American actor known for his roles in major television series such as "Game of Thrones," "Narcos," and "The Mandalorian," as well as various high-profile films.
  • C. Marc Tarpenning
    Marc Tarpenning is an American engineer and entrepreneur best known as a co-founder of electric vehicle and clean energy company Tesla, Inc.
  • D. Jeremy Irvine
    Jeremy Irvine is an English actor best known for his breakout role in Steven Spielberg’s "War Horse" and subsequent performances in films such as "The Railway Man."
  • E. Adam Driver
    Adam Driver is an American actor acclaimed for his intense, versatile performances in film, television, and theater, including prominent roles in "Girls," the "Star Wars" sequel trilogy, and numerous critically lauded dramas.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d776c6c819081b41a9b55041cd5 completed March 1, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5216e11248190a8c564a482d649a6 completed March 2, 2026, 5:34 a.m.
Created at: March 1, 2026, 7:35 p.m.