Triple
T19294229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arrondissement of Largentière |
E482519
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Largentière |
—
|
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: Largentière | Statement: [arrondissement of Largentière, administrativeCenter, Largentière]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Largentière Context triple: [arrondissement of Largentière, administrativeCenter, Largentière]
-
A.
Largentière
chosen
Largentière is a historic town in southern France known for its medieval architecture and former silver mining industry.
-
B.
Casseneuil
Casseneuil is a small commune in southwestern France, located in the Lot-et-Garonne department in the Nouvelle-Aquitaine region.
-
C.
Assencières
Assencières is a small commune in the Aube department of north-central France.
-
D.
Aiguillon
Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
-
E.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc84500c81908ac53711335ad2d9 |
completed | April 20, 2026, 10:14 a.m. |
Created at: April 10, 2026, 1:31 p.m.