Triple
T21016186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wasseramt region |
E517681
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Lohn-Ammannsegg |
—
|
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: Lohn-Ammannsegg | Statement: [Wasseramt region, containsMunicipality, Lohn-Ammannsegg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lohn-Ammannsegg Context triple: [Wasseramt region, containsMunicipality, Lohn-Ammannsegg]
-
A.
Lohn-Ammannsegg
chosen
Lohn-Ammannsegg is a municipality in the canton of Solothurn in Switzerland, known for its residential character and proximity to the city of Solothurn.
-
B.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
C.
Zauggenried
Zauggenried was a former Swiss municipality in the canton of Bern that has been incorporated into the larger municipality of Fraubrunnen.
-
D.
Bonstetten
Bonstetten is a small municipality in the Swabian region of Bavaria in southern Germany.
-
E.
Eggenwil
Eggenwil is a small municipality in the canton of Aargau in northern Switzerland, situated near the Reuss River and characterized by its rural, village-like setting.
- 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_69e0b50262b081909bc488937145eb73 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc58272881908a61eda7755ed332 |
completed | April 21, 2026, 4:26 a.m. |
Created at: April 16, 2026, 1:54 p.m.