Triple
T9528871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solothurn-Lebern region |
E229831
|
entity |
| Predicate | hasPrimaryCity |
P3940
|
FINISHED |
| Object | Solothurn |
E22880
|
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: Solothurn | Statement: [Solothurn-Lebern region, hasPrimaryCity, Solothurn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Solothurn Context triple: [Solothurn-Lebern region, hasPrimaryCity, Solothurn]
-
A.
Solothurn
chosen
Solothurn is a canton in northwestern Switzerland known for its historic baroque town of the same name and its location along the Aare River.
-
B.
Schaffhausen
Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
-
C.
Grenchen
Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
-
D.
Türnich
Türnich is a district of the town of Kerpen in North Rhine-Westphalia, Germany, known as a residential area within the Cologne metropolitan region.
-
E.
Neuchâtel
Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
- 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_69ca8479934c81908006d0e6e970ae05 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98b1b93481909812245ac14e4988 |
completed | April 1, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc35038081909f5cf3f148e95541 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8 p.m.