Triple

T11736288
Position Surface form Disambiguated ID Type / Status
Subject Madeleine Talmage Force E279034 entity
Predicate givenName P17 FINISHED
Object Madeleine E215457 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: Madeleine | Statement: [Madeleine Talmage Force, givenName, Madeleine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madeleine
Context triple: [Madeleine Talmage Force, givenName, Madeleine]
  • A. Madeleine chosen
    Madeleine is a feminine given name, commonly used in French and English, derived from Magdalene and often associated with literary and cultural figures.
  • B. Madeleine
    Madeleine is a Paris Métro station in central Paris that serves as an interchange between several metro lines, including the automated Line 14.
  • C. Madelaine
    Madelaine is a character in the Danish crime thriller film "The Salvation."
  • D. 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.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4edced48190b7a59dd45921828e completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019b318188190bfb7effcf42974d2 completed April 28, 2026, 2:21 a.m.
Created at: April 8, 2026, 9:41 p.m.