Triple

T12135608
Position Surface form Disambiguated ID Type / Status
Subject Letitia E289047 entity
Predicate hasVariant P455 FINISHED
Object Laetitia E236777 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: Laetitia | Statement: [Letitia, hasVariant, Laetitia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laetitia
Context triple: [Letitia, hasVariant, Laetitia]
  • A. Laetitia chosen
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • B. Bénédicte
    Bénédicte is the given name of Louise Bénédicte de Bourbon, a French noblewoman of the House of Bourbon.
  • C. Léa
    Léa is a French feminine given name commonly used in Francophone countries.
  • D. Armande
    Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
  • E. Françoise
    Françoise is a central character in Éric Rohmer’s film "My Night at Maud’s," representing the devout, idealized young woman with whom the protagonist becomes romantically involved.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158c59e0819094d4522a107482b2 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e4a573c8190b5dd6cc61849739b completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:49 p.m.