Triple

T8438000
Position Surface form Disambiguated ID Type / Status
Subject Tiphaine Auzière E199276 entity
Predicate givenName P17 FINISHED
Object Tiphaine
Tiphaine is a French given name, notably borne by Tiphaine Auzière, the daughter of Brigitte Macron.
 E733397 NE FINISHED

How this triple was built (4 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: Tiphaine | Statement: [Tiphaine Auzière, givenName, Tiphaine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tiphaine
Context triple: [Tiphaine Auzière, givenName, Tiphaine]
  • A. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • B. Yvaine
    Yvaine is the fallen star and central heroine of Neil Gaiman’s fantasy novel (and its film adaptation) "Stardust," whose journey intertwines magic, romance, and adventure.
  • C. Azélie
    Azélie is a short story by Kate Chopin, included in her 1897 collection *A Night in Acadie*, that explores themes of love, culture, and identity in a Louisiana setting.
  • D. Noémie
    Noémie is a French given name, equivalent to Naomi, commonly used for girls in Francophone countries.
  • E. Delphine
    Delphine is an epistolary novel by Madame de Staël that explores themes of love, social convention, and women's independence in late 18th-century French society.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tiphaine
Triple: [Tiphaine Auzière, givenName, Tiphaine]
Generated description
Tiphaine is a French given name, notably borne by Tiphaine Auzière, the daughter of Brigitte Macron.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tiphaine
Target entity description: Tiphaine is a French given name, notably borne by Tiphaine Auzière, the daughter of Brigitte Macron.
  • A. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • B. Yvaine
    Yvaine is the fallen star and central heroine of Neil Gaiman’s fantasy novel (and its film adaptation) "Stardust," whose journey intertwines magic, romance, and adventure.
  • C. Azélie
    Azélie is a short story by Kate Chopin, included in her 1897 collection *A Night in Acadie*, that explores themes of love, culture, and identity in a Louisiana setting.
  • D. Noémie
    Noémie is a French given name, equivalent to Naomi, commonly used for girls in Francophone countries.
  • E. Delphine
    Delphine is an epistolary novel by Madame de Staël that explores themes of love, social convention, and women's independence in late 18th-century French society.
  • F. None of above. chosen

Provenance (5 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_69ca8314cd6c8190a6b8c2a1096e18f3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe13446788190ad52a4fd6e8b498a completed March 31, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d87403c8190b979af4979e43517 completed April 2, 2026, 7:40 a.m.
NEDg Description generation batch_69ce1f12e1a081909d28b06c520353ef completed April 2, 2026, 7:47 a.m.
NED2 Entity disambiguation (via description) batch_69ce1fb498448190a2737b8895f6bb48 completed April 2, 2026, 7:50 a.m.
Created at: March 30, 2026, 6:08 p.m.