Triple

T15089579
Position Surface form Disambiguated ID Type / Status
Subject Valentine de Villefort E360380 entity
Predicate givenName P17 FINISHED
Object Valentine E113659 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: Valentine | Statement: [Valentine de Villefort, givenName, Valentine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valentine
Context triple: [Valentine de Villefort, givenName, Valentine]
  • A. Valentine chosen
    Valentine is a masculine given name of Latin origin commonly associated with the meaning "strong" or "healthy" and historically linked to Saint Valentine.
  • B. Valentine
    "Valentine" is a popular song famously performed by French entertainer Maurice Chevalier, showcasing his signature romantic and charming style.
  • C. Valentine
    Valentine is the primary antagonist in the film "Kingsman: The Secret Service," a wealthy and eccentric tech billionaire who devises a global genocide plot under the guise of environmentalism.
  • D. Valentine
    Valentine is a small commune in southwestern France, located in the Haute-Garonne department within the Occitanie region.
  • E. Valentine
    "Valentine" is a romantic novel by French writer George Sand that explores themes of love, class, and social convention in 19th-century rural France.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00277ea808190be3f002a8316eff1 completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae1d7a0c819096b035f8ca8d0e90 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:04 a.m.