Triple

T16281590
Position Surface form Disambiguated ID Type / Status
Subject Francesco Esposito E395274 entity
Predicate etymologicallyRelatedGivenName P108324 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: [Francesco Esposito, etymologicallyRelatedGivenName, François]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: François
Context triple: [Francesco Esposito, etymologicallyRelatedGivenName, 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24910c6b881909ae5cc0908dd8eb2 completed April 17, 2026, 2:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017c6b72081908a21e5099f463b62 completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:05 a.m.