Triple
T7367181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brigitte Macron |
E169899
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Trogneux |
E631616
|
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: Trogneux | Statement: [Brigitte Macron, familyName, Trogneux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trogneux Context triple: [Brigitte Macron, familyName, Trogneux]
-
A.
Trogneux
chosen
Trogneux is a French surname notably borne by Brigitte Macron, the First Lady of France.
-
B.
Tignère
Tignère is a town and commune located in Cameroon's Adamawa Region, known for its highland setting and role as a local administrative and trading center.
-
C.
Thieux
Thieux is a small French commune located in the Seine-et-Marne department in the Île-de-France region in north-central France.
-
D.
Carcagny
Carcagny is a small commune in the Calvados department of the Normandy region in northwestern France.
-
E.
Vauvert
Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
- 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.