Triple
T1558645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avully |
E33266
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Geneva countryside |
E71723
|
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: Geneva countryside | Statement: [Avully, region, Geneva countryside]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geneva countryside Context triple: [Avully, region, Geneva countryside]
-
A.
La Sarraz, Switzerland
La Sarraz, Switzerland is a small historic town in the canton of Vaud known for its medieval castle and its role in early 20th-century modern architecture movements.
-
B.
Montgenèvre
Montgenèvre is a French Alpine ski resort village in the Hautes-Alpes department, known for its high-altitude slopes and location near the Italian border.
-
C.
Chêne-Bougeries
Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
-
D.
Saignelégier
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
-
E.
Bardonnex
chosen
Bardonnex is a small Swiss municipality located in the canton of Geneva, near the country’s border with France.
- 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa621102cc81909c5b777a105fc91c |
completed | March 6, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad3710688c8190a280f03bced5601f |
completed | March 8, 2026, 8:45 a.m. |
Created at: March 4, 2026, 7:27 p.m.