Triple
T7474618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Constance |
E176598
|
entity |
| Predicate | bordersCity |
P224
|
FINISHED |
| Object | Romanshorn |
E524736
|
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: Romanshorn | Statement: [Lake Constance, bordersCity, Romanshorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Romanshorn Context triple: [Lake Constance, bordersCity, Romanshorn]
-
A.
Romanshorn
chosen
Romanshorn is a Swiss town on the southern shore of Lake Constance, known as an important regional transport hub and ferry port.
-
B.
Ramiswil
Ramiswil is a small rural municipality in the canton of Solothurn in northwestern Switzerland, known for its scenic Jura landscape and agricultural character.
-
C.
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.
-
D.
Landquart
Landquart is a river in eastern Switzerland that flows through the canton of Graubünden before joining the Alpine Rhine.
-
E.
Schaffhausen
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.
- 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_69c69f236ce08190a04d7679f03b29b2 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f417fbb48190b134eaf1da1b4289 |
completed | March 27, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9494351488190852b600d9666d1eb |
completed | March 29, 2026, 3:46 p.m. |
Created at: March 27, 2026, 3:41 p.m.