Triple

T19055057
Position Surface form Disambiguated ID Type / Status
Subject Carlo Ventresca E466371 entity
Predicate creator P184 FINISHED
Object Dan Brown 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: Dan Brown | Statement: [Carlo Ventresca, creator, Dan Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Brown
Context triple: [Carlo Ventresca, creator, Dan Brown]
  • A. Dan Brown chosen
    Dan Brown is an American author best known for his fast-paced mystery thrillers that blend historical, religious, and conspiracy themes, including the bestselling novel "The Da Vinci Code."
  • B. Robert Ludlum
    Robert Ludlum was an American author best known for his fast-paced espionage and thriller novels, including the Jason Bourne series.
  • C. Nicholas Evans
    Nicholas Evans was a British author best known for his bestselling novel "The Horse Whisperer," which was adapted into a major film.
  • D. Anthony Horowitz
    Anthony Horowitz is a British novelist and screenwriter best known for his Alex Rider spy novels and numerous television crime dramas.
  • E. Jonathan Harr
    Jonathan Harr is an American author and journalist best known for his nonfiction legal thriller "A Civil Action," which chronicles a landmark environmental lawsuit.
  • 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_69d8dd040fb881909af2a964f65ad208 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5dc056b708190a2b84cbddf0fc2d9 completed April 20, 2026, 7:55 a.m.
Created at: April 10, 2026, 12:03 p.m.