Triple
T6726789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alphubel |
E153536
|
entity |
| Predicate | normalRouteFrom |
P32243
|
FINISHED |
| Object | Täschalp |
E400977
|
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: Täschalp | Statement: [Alphubel, normalRouteFrom, Täschalp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Täschalp Context triple: [Alphubel, normalRouteFrom, Täschalp]
-
A.
Bettlach
Bettlach is a Swiss municipality located in the canton of Solothurn.
-
B.
Oberegg
Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
-
C.
Aarberg
Aarberg is a small historic town in the canton of Bern in Switzerland, known for its medieval center and distinctive wooden bridge over the Aare River.
-
D.
Seckbach
Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
-
E.
Kiental
chosen
Kiental is a picturesque alpine valley and village in the Bernese Oberland region of Switzerland, known for its dramatic mountain scenery and hiking opportunities.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d152a4908190a041f2049240e7ca |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70afea37881909a4fdce4b3229e38 |
completed | March 27, 2026, 10:55 p.m. |
Created at: March 27, 2026, 2:08 p.m.