Triple
T16222779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winterthur railway station |
E393769
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Schaffhausen |
E183831
|
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: Schaffhausen | Statement: [Winterthur railway station, connectsTo, Schaffhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schaffhausen Context triple: [Winterthur railway station, connectsTo, Schaffhausen]
-
A.
Schaffhausen
chosen
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.
-
B.
Schafhausen
Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
-
C.
Luzern
Luzern is a picturesque Swiss city on Lake Lucerne, renowned for its preserved medieval architecture, iconic Chapel Bridge, and surrounding mountain scenery.
-
D.
Solothurn
Solothurn is a canton in northwestern Switzerland known for its historic baroque town of the same name and its location along the Aare River.
-
E.
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.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e227fcf058819099d5ff965cc2c267 |
completed | April 17, 2026, 12:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00354a20d081908288fb8c0e8b83b6 |
completed | May 10, 2026, 7:35 a.m. |
Created at: April 10, 2026, 5:03 a.m.