Triple

T8020169
Position Surface form Disambiguated ID Type / Status
Subject Aurore Giscard d’Estaing E186719 entity
Predicate givenName P17 FINISHED
Object Aurore
Aurore is a French given name commonly used for women, derived from the Latin word for "dawn."
 E708754 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: Aurore | Statement: [Aurore Giscard d’Estaing, givenName, Aurore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aurore
Context triple: [Aurore Giscard d’Estaing, givenName, Aurore]
  • A. Juliette
    Juliette is a feminine given name of French origin, widely used in many countries and popularized through literature and film.
  • B. 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.
  • C. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • D. Odile
    Odile is the seductive and deceptive Black Swan character in the ballet "Swan Lake," often portrayed as the antagonist and foil to the virtuous Odette.
  • E. 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.
  • 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: Aurore
Triple: [Aurore Giscard d’Estaing, givenName, Aurore]
Generated description
Aurore is a French given name commonly used for women, derived from the Latin word for "dawn."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aurore
Target entity description: Aurore is a French given name commonly used for women, derived from the Latin word for "dawn."
  • A. Juliette
    Juliette is a feminine given name of French origin, widely used in many countries and popularized through literature and film.
  • B. 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.
  • C. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • D. Odile
    Odile is the seductive and deceptive Black Swan character in the ballet "Swan Lake," often portrayed as the antagonist and foil to the virtuous Odette.
  • E. 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.
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3e8bc90081909f6f5878e6f1f241 completed March 31, 2026, 3:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56c82824819082e93eddc40bfad1 completed March 31, 2026, 11:20 p.m.
NEDg Description generation batch_69cc5ca6efbc819082f4c643446da354 completed March 31, 2026, 11:45 p.m.
NED2 Entity disambiguation (via description) batch_69cc5d6d93f08190b17d6c7a4fad2cf0 completed March 31, 2026, 11:49 p.m.
Created at: March 30, 2026, 5:20 p.m.