Triple

T10155532
Position Surface form Disambiguated ID Type / Status
Subject Régine Chassagne E232766 entity
Predicate givenName P17 FINISHED
Object Régine E662578 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: Régine | Statement: [Régine Chassagne, givenName, Régine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Régine
Context triple: [Régine Chassagne, givenName, Régine]
  • A. Françoise
    Françoise is the given name of Louise de La Vallière, a 17th-century French noblewoman best known as a mistress of King Louis XIV.
  • B. 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.
  • C. Regine chosen
    Regine is a feminine given name of Latin origin, commonly used in various European countries and associated with figures such as Regine Olsen, the onetime fiancée of philosopher Søren Kierkegaard.
  • D. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • E. Valérie
    Valérie is a French feminine given name commonly used in Francophone countries.
  • 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_69ca84885e48819088a31b127cf44904 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec3a5e7c819098b2f9ccbde7cf94 completed April 2, 2026, 4:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e65b9d4c8190b1f520ed08256372 completed April 5, 2026, 10:46 p.m.
Created at: March 30, 2026, 9:09 p.m.