Triple

T1379037
Position Surface form Disambiguated ID Type / Status
Subject Brigitte Macron E29294 entity
Predicate givenName P17 FINISHED
Object Brigitte
Brigitte is a French former teacher best known as the wife of Emmanuel Macron, the President of France.
E169899 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: Brigitte | Statement: [Brigitte Macron, givenName, Brigitte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brigitte
Context triple: [Brigitte Macron, givenName, Brigitte]
  • A. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • B. Micheline
    Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
  • C. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • 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. Jane Avril
    Jane Avril is a famous poster by French artist Henri de Toulouse-Lautrec depicting the celebrated can-can dancer of the Moulin Rouge.
  • 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: Brigitte
Triple: [Brigitte Macron, givenName, Brigitte]
Generated description
Brigitte is a French former teacher best known as the wife of Emmanuel Macron, the President of France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Brigitte
Target entity description: Brigitte is a French former teacher best known as the wife of Emmanuel Macron, the President of France.
  • A. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • B. Micheline
    Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
  • C. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • 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. Jane Avril
    Jane Avril is a famous poster by French artist Henri de Toulouse-Lautrec depicting the celebrated can-can dancer of the Moulin Rouge.
  • 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_69a498d883a48190bfdca525296ef7ee completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c3187f248190a5813274b0ef944d completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1c97ba748190a227457bcb87a733 completed March 8, 2026, 6:52 a.m.
NEDg Description generation batch_69ad1d1eccfc81909bdf4df141d1987f completed March 8, 2026, 6:54 a.m.
NED2 Entity disambiguation (via description) batch_69ad1d8cea008190be2557f6804a261f completed March 8, 2026, 6:56 a.m.
Created at: March 1, 2026, 7:59 p.m.