Triple
T2647441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ain |
E53817
|
entity |
| Predicate | subprefecture |
P9697
|
FINISHED |
| Object | Belley |
E280234
|
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: Belley | Statement: [Ain, subprefecture, Belley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belley Context triple: [Ain, subprefecture, Belley]
-
A.
Belley
chosen
Belley is a historic town in eastern France that serves as one of the administrative centers of the Ain department in the Auvergne-Rhône-Alpes region.
-
B.
La Baille
La Baille is the traditional nickname for the French Naval Academy, the institution responsible for training officers of the French Navy.
-
C.
Valleiry
Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
-
D.
Choully
Choully is a small wine-producing village in the commune of Satigny in the canton of Geneva, Switzerland.
-
E.
Louvois
Louvois was a powerful French statesman, best known as Louis XIV’s influential war minister who significantly shaped France’s military administration in the late 17th century.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd919bf2c81908feb768f3391e985 |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98c721b08190b380d3625126cb55 |
completed | March 10, 2026, 4:06 a.m. |
Created at: March 6, 2026, 9:53 p.m.