Triple
T17868127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eich |
E446758
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Nottwil |
—
|
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: Nottwil | Statement: [Eich, hasNeighboringMunicipality, Nottwil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nottwil Context triple: [Eich, hasNeighboringMunicipality, Nottwil]
-
A.
Nottwil
chosen
Nottwil is a Swiss municipality in the canton of Lucerne, known for its lakeside location and the Swiss Paraplegic Centre.
-
B.
Garrweiler
Garrweiler is a small village that forms one of the constituent districts of the town of Altensteig in the German state of Baden-Württemberg.
-
C.
Sarnen
Sarnen is a Swiss town in central Switzerland that serves as the administrative and economic center of the canton of Obwalden, situated on the shores of Lake Sarnen amid alpine scenery.
-
D.
Schmerikon
Schmerikon is a municipality in the canton of St. Gallen in Switzerland, situated on the shores of Lake Zurich.
-
E.
Wolfisberg
Wolfisberg is a small Swiss municipality in the canton of Bern, known for its rural setting in the Oberaargau region.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa0b69081909fba3b42d237b543 |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 10:17 a.m.