Triple
T20188529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Loménie |
E492924
|
entity |
| Predicate | hasSeat |
P3522
|
FINISHED |
| Object | Brienne-le-Château |
—
|
NE NERFINISHED |
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: Brienne-le-Château | Statement: [House of Loménie, hasSeat, Brienne-le-Château]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brienne-le-Château Context triple: [House of Loménie, hasSeat, Brienne-le-Château]
-
A.
Brienne-le-Château
chosen
Brienne-le-Château is a commune in northeastern France best known as the town where Napoleon Bonaparte attended military school in his youth.
-
B.
Magnicourt
Magnicourt is a small French commune located in the Aube department in the Grand Est region of northeastern France.
-
C.
Château de Brienne
Château de Brienne is a historic French castle in the town of Brienne-le-Château, notably associated with Napoleon Bonaparte’s early military education.
-
D.
Châteaurenault
Châteaurenault was a notable 17th-century French naval officer and admiral who played a key role in several major maritime conflicts of his time.
-
E.
Courcouronnes
Courcouronnes is a suburban commune in the southern Île-de-France region of France, located in the Essonne department near Paris.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad404508190981cfb7cab18d8d3 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:37 p.m.