Triple

T5776322
Position Surface form Disambiguated ID Type / Status
Subject César Franck E127450 entity
Predicate familyName P18 FINISHED
Object Franck E172426 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: Franck | Statement: [César Franck, familyName, Franck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franck
Context triple: [César Franck, familyName, Franck]
  • A. Franck chosen
    Franck is a surname most notably associated with James Franck, the German physicist and Nobel laureate recognized for the Franck–Hertz experiment.
  • B. Royer
    Royer was a costume designer known for his work on classic Hollywood films, including the 1939 drama "The Rains Came."
  • C. Franck Leroy
    Franck Leroy is a French politician known for serving as the mayor of Épernay, a commune in the Marne department of northeastern France.
  • D. Fernand
    Fernand is a given name, primarily used in French and other Romance-language contexts, that corresponds to the name Ferdinand.
  • E. Firmin
    Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029de3bb4819087a6f3e920e12990 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e6fd260819090d5e3c877c8bd31 completed March 22, 2026, 11:42 p.m.
Created at: March 22, 2026, 3:50 p.m.