Triple

T19656304
Position Surface form Disambiguated ID Type / Status
Subject François de Bourbon, Count of Enghien E471952 entity
Predicate givenName P17 FINISHED
Object François 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: François | Statement: [François de Bourbon, Count of Enghien, givenName, François]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: François
Context triple: [François de Bourbon, Count of Enghien, givenName, François]
  • A. François
    François is the given name of the French poet and essayist Sully Prudhomme, the first recipient of the Nobel Prize in Literature.
  • B. François
    François is a central character in Claude Chabrol’s 1958 French New Wave film "Le Beau Serge," whose troubled life and relationships drive much of the drama.
  • C. François
    François is the French given name of Francis Carco, a 20th-century French novelist, poet, and journalist known for his portrayals of Parisian underworld life.
  • D. François
    François is a French given name historically borne by notable figures such as Marshal Luxembourg, reflecting its long-standing prominence in Francophone cultures.
  • E. François chosen
    François is a French masculine given name historically borne by numerous notable figures in politics, arts, and literature.
  • 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_69d8e51395348190ac1416d46dfc6db0 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64146539c8190813debb0d964bc23 completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:45 p.m.