Triple

T10480748
Position Surface form Disambiguated ID Type / Status
Subject Ibn Tufayl E247161 entity
Predicate influenced P9 FINISHED
Object Daniel Defoe E23892 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: Daniel Defoe | Statement: [Ibn Tufayl, influenced, Daniel Defoe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Defoe
Context triple: [Ibn Tufayl, influenced, Daniel Defoe]
  • A. Daniel Defoe chosen
    Daniel Defoe was an English writer, journalist, and pamphleteer best known as a pioneer of the novel form and the author of "Robinson Crusoe."
  • B. John Bunyan
    John Bunyan was a 17th-century English Puritan preacher and writer best known for his Christian allegory "The Pilgrim's Progress."
  • C. Jonathan Swift
    Jonathan Swift was an Anglo-Irish satirist, essayist, and clergyman best known for works like "Gulliver’s Travels" and "A Modest Proposal," which sharply critiqued politics and society.
  • D. Henry Fielding
    Henry Fielding was an 18th-century English novelist and dramatist best known for his satirical works such as "Tom Jones," which helped shape the development of the modern novel.
  • E. Tobias Smollett
    Tobias Smollett was an 18th-century Scottish novelist, satirist, and physician best known for his picaresque novels and sharp social commentary.
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5095c5dc88190902582db28df01b4 completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8a02aa2748190902f5c08afd7dda9 completed April 10, 2026, 7 a.m.
Created at: April 6, 2026, 12:22 p.m.