Triple

T20415120
Position Surface form Disambiguated ID Type / Status
Subject Red Dog E500691 entity
Predicate originalWorkAuthor P23529 FINISHED
Object Louis de Bernières 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: Louis de Bernières | Statement: [Red Dog, originalWorkAuthor, Louis de Bernières]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis de Bernières
Context triple: [Red Dog, originalWorkAuthor, Louis de Bernières]
  • A. Louis de Bernières chosen
    Louis de Bernières is a British novelist best known for works such as "Captain Corelli’s Mandolin" and the novella "Red Dog," which inspired the film of the same name.
  • B. Sebastian Faulks
    Sebastian Faulks is a British novelist best known for his historical and war-themed fiction, including the acclaimed novel "Birdsong."
  • C. William Boyd
    William Boyd was an American actor best known for portraying the cowboy hero Hopalong Cassidy in numerous films and early television.
  • D. William Boyd
    William Boyd is a Scottish novelist and screenwriter acclaimed for his richly crafted literary fiction, including works such as "Any Human Heart" and "A Good Man in Africa."
  • E. C.J. Sansom
    C.J. Sansom was a British historical crime novelist best known for his bestselling Shardlake series set in Tudor England.
  • 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_69e0b4a935588190b9446a99b37ced44 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67a437eec8190a20c89a236dd5bc0 completed April 20, 2026, 7:10 p.m.
Created at: April 16, 2026, 11:30 a.m.