Triple

T17606317
Position Surface form Disambiguated ID Type / Status
Subject Francis E428840 entity
Predicate hasVariant P455 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: [Francis, hasVariant, François]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: François
Context triple: [Francis, hasVariant, François]
  • A. 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.
  • B. 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.
  • C. François
    François is a French given name historically borne by notable figures such as Marshal Luxembourg, reflecting its long-standing prominence in Francophone cultures.
  • D. François
    François is the given name of Chevalier de Lévis, an 18th-century French nobleman and military commander who served in New France during the Seven Years' War.
  • E. François
    François is the given name of the French poet and essayist Sully Prudhomme, the first recipient of the Nobel Prize in Literature.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46c4c06a88190a0be2dec3d6056c4 completed April 19, 2026, 5:46 a.m.
Created at: April 10, 2026, 5:51 a.m.