Triple
T21903992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S4 line |
E540882
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Langnau-Gattikon |
—
|
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: Langnau-Gattikon | Statement: [S4 line, connects, Langnau-Gattikon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langnau-Gattikon Context triple: [S4 line, connects, Langnau-Gattikon]
-
A.
Langnau-Gattikon
chosen
Langnau-Gattikon is a municipality in the canton of Zurich, Switzerland, located in the Sihl Valley and integrated into the Zurich S-Bahn commuter rail network.
-
B.
Zauggenried
Zauggenried was a former Swiss municipality in the canton of Bern that has been incorporated into the larger municipality of Fraubrunnen.
-
C.
Küsnacht
Küsnacht is a picturesque Swiss municipality on the shores of Lake Zurich, known for its affluent residential character and scenic lakeside setting.
-
D.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
E.
Güglingen
Güglingen is a small town in the German state of Baden-Württemberg, known for its wine-growing tradition and location in the Zabergäu 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f121d4c0248190909172decd7cbc64 |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 16, 2026, 7:26 p.m.