Triple
T10982380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scharmützelsee |
E259539
|
entity |
| Predicate | hasShoreSettlement |
P16159
|
FINISHED |
| Object | Bad Saarow |
E898023
|
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: Bad Saarow | Statement: [Scharmützelsee, hasShoreSettlement, Bad Saarow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Saarow Context triple: [Scharmützelsee, hasShoreSettlement, Bad Saarow]
-
A.
Bad Saarow
chosen
Bad Saarow is a German spa town in Brandenburg known for its thermal baths and lakeside setting on the Scharmützelsee.
-
B.
Bad Camberg
Bad Camberg is a German spa town in the state of Hesse, known for its historic half-timbered old town and therapeutic health resorts.
-
C.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
D.
Bad Tennstedt
Bad Tennstedt is a small spa town in Thuringia, Germany, known for its mineral springs and location in the Unstrut river landscape.
-
E.
Bad Iburg
Bad Iburg is a small spa town in Lower Saxony, Germany, known for its historic Iburg Castle and surrounding Teutoburg Forest scenery.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d772eb518c8190a885a417815f2ff6 |
completed | April 9, 2026, 9:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e374526d54819085a0fb0d62f7a581 |
completed | April 18, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:24 p.m.