Triple

T3321533
Position Surface form Disambiguated ID Type / Status
Subject Never Say Never Again E69805 entity
Predicate basedOnWorkBy P2806 FINISHED
Object Ian Fleming E3433 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: Ian Fleming | Statement: [Never Say Never Again, basedOnWorkBy, Ian Fleming]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ian Fleming
Context triple: [Never Say Never Again, basedOnWorkBy, Ian Fleming]
  • A. Ian Fleming chosen
    Ian Fleming was a British author and journalist best known as the creator of the James Bond spy novels.
  • B. John le Carré
    John le Carré was a renowned British novelist best known for his sophisticated espionage thrillers that explored the moral ambiguities of Cold War intelligence work.
  • C. William Fleming
    William Fleming is a relatively common personal name shared by multiple notable individuals across fields such as politics, education, and sports.
  • D. Peter Fleming
    Peter Fleming was a British travel writer, journalist, and adventurer, best known for his travel books and for his work as a wartime intelligence officer.
  • E. Alistair MacLean
    Alistair MacLean was a Scottish novelist best known for his fast-paced World War II and Cold War adventure thrillers, many of which were adapted into popular films.
  • 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_69ad85a1829881908942c14075644d0d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb13b85208190b13aba355d5dafcf completed March 8, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a7954248190b0c7b5d6ab3c6687 completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:11 p.m.