Triple
T7059597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charolais |
E164180
|
entity |
| Predicate | hasNameOrigin |
P3325
|
FINISHED |
| Object | Charolles |
E234344
|
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: Charolles | Statement: [Charolais, hasNameOrigin, Charolles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charolles Context triple: [Charolais, hasNameOrigin, Charolles]
-
A.
Charolles
chosen
Charolles is a small historic town in eastern France, known as the traditional capital of the Charolais cattle-breeding region.
-
B.
Plombières
Plombières is a municipality in the province of Liège in eastern Belgium, near the German and Dutch borders.
-
C.
Chiroubles
Chiroubles is a French appellation in the Beaujolais region known for producing light, aromatic red wines primarily from the Gamay grape.
-
D.
Gueugnon
Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
-
E.
Cugny
Cugny is a locality within the municipality of Bernex in the canton of Geneva, Switzerland.
- 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_69c688796c148190adb2f1596f595f22 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c845d90b48819081280063dcaafad7 |
completed | March 28, 2026, 9:19 p.m. |
Created at: March 27, 2026, 2:38 p.m.