Triple

T5453894
Position Surface form Disambiguated ID Type / Status
Subject Donald Grant E122431 entity
Predicate alias P39 FINISHED
Object Red Grant E126240 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: Red Grant | Statement: [Donald Grant, alias, Red Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Red Grant
Context triple: [Donald Grant, alias, Red Grant]
  • A. Red Grant chosen
    Red Grant is a ruthless, psychopathic assassin and primary antagonist in the James Bond franchise, most prominently appearing as SPECTRE’s top killer in the film and novel "From Russia, with Love."
  • B. Lawrence Grant
    Lawrence Grant was a British character actor known for his supporting roles in early 20th-century Hollywood films.
  • C. Gilbert Roberts
    Gilbert Roberts was a prominent British civil engineer renowned for designing major long-span bridges in the mid-20th century.
  • D. Gilbert Roberts
    Gilbert Roberts was a British Royal Navy officer and tactical innovator best known for developing anti-U-boat convoy tactics during World War II.
  • E. Grant Withers
    Grant Withers was an American film actor known for his prolific work in Hollywood from the silent era through the 1950s, often appearing in Westerns and crime 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_69bd46424248819085282ddf50a565f3 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91ed9a388190967e7ffaf9dbadc6 completed March 20, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4140248081908c7f42b91579a837 completed March 22, 2026, 1:09 a.m.
Created at: March 20, 2026, 2:08 p.m.