Triple

T11994320
Position Surface form Disambiguated ID Type / Status
Subject Paulette Jiles E285488 entity
Predicate hasWritten P2831 FINISHED
Object Simon the Fiddler E958687 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: Simon the Fiddler | Statement: [Paulette Jiles, hasWritten, Simon the Fiddler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simon the Fiddler
Context triple: [Paulette Jiles, hasWritten, Simon the Fiddler]
  • A. Simon the Fiddler chosen
    Simon the Fiddler is a historical novel by Paulette Jiles that follows a young fiddler navigating love, survival, and shifting loyalties in the chaotic aftermath of the American Civil War.
  • B. Phil the Fiddler
    Phil the Fiddler is a 19th-century juvenile novel by Horatio Alger Jr. that follows an Italian street musician’s struggles and pursuit of the American Dream in New York City.
  • C. Symon
    Symon is a given name most notably borne by Symon Petliura, a Ukrainian political leader and statesman of the early 20th century.
  • D. The Bagpiper
    The Bagpiper is a genre painting by Dutch Golden Age artist Abraham Bloemaert depicting a rustic musician playing the bagpipes.
  • E. Francis the Talking Mule
    Francis the Talking Mule is a comedic, wisecracking military mule character from a popular 1950s film series, known for speaking only to a befuddled soldier and getting him into and out of trouble.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903b211688190bfe6dd15c3f96d2f completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48ad06350819094180403858db172 completed May 1, 2026, 11:13 a.m.
Created at: April 8, 2026, 9:46 p.m.