Triple
T9545128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Dôle |
E230261
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Saint-Cergue |
E437782
|
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: Saint-Cergue | Statement: [La Dôle, near, Saint-Cergue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Cergue Context triple: [La Dôle, near, Saint-Cergue]
-
A.
Saint-Cergue
chosen
Saint-Cergue is a Swiss mountain municipality in the canton of Vaud, known for its scenic Jura landscapes and outdoor recreational activities.
-
B.
Céligny
Céligny is a small, affluent Swiss village on the shores of Lake Geneva, known for its picturesque setting and as the burial place of actor Richard Burton.
-
C.
Delémont
Delémont is a historic town in northwestern Switzerland that serves as the capital of the canton of Jura.
-
D.
Saint-Prex
Saint-Prex is a picturesque medieval town on the shores of Lake Geneva in the canton of Vaud, Switzerland, known for its historic old town and lakeside setting.
-
E.
Hermance
Hermance is a small lakeside municipality on the shores of Lake Geneva in southwestern 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9901f2bc8190a4076f5947660df9 |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c6cd93c8190ac197afda780ce78 |
completed | April 4, 2026, 5:37 p.m. |
Created at: March 30, 2026, 8:01 p.m.