Triple

T16027834
Position Surface form Disambiguated ID Type / Status
Subject Philippe-François-Nazaire Fabre d’Églantine E388763 entity
Predicate givenName P17 FINISHED
Object François E1132436 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: François | Statement: [Philippe-François-Nazaire Fabre d’Églantine, givenName, François]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: François
Context triple: [Philippe-François-Nazaire Fabre d’Églantine, 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 (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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183294984819080b8727a3511a21b completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbcfd39c81909bfddfe95f9ad7d2 completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 4:56 a.m.