Triple
T7367179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brigitte Macron |
E169899
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Brigitte Marie-Claude Trogneux |
E160755
|
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: Brigitte Marie-Claude Trogneux | Statement: [Brigitte Macron, birthName, Brigitte Marie-Claude Trogneux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brigitte Marie-Claude Trogneux Context triple: [Brigitte Macron, birthName, Brigitte Marie-Claude Trogneux]
-
A.
Brigitte Marie-Claude Trogneux
chosen
Brigitte Marie-Claude Trogneux is a French former teacher and the First Lady of France, married to President Emmanuel Macron.
-
B.
Claudie Haigneré
Claudie Haigneré is a French physician, astronaut, and former government minister who became the first French woman in space and a prominent figure in European space exploration.
-
C.
Nelly Auteuil
Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
-
D.
Melanie Thierry
Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
-
E.
Sandrine Kiberlain
Sandrine Kiberlain is a French actress and singer known for her acclaimed performances in both dramatic and comedic films.
- 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_69c68a5ade988190885b7175f63b7534 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f17ea0608190955ac3474f6da7bb |
completed | March 27, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802bc25908190ad444de63b7526a0 |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:06 p.m.