Triple
T23372600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schulpforta |
E593513
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Bad Kösen |
—
|
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: Bad Kösen | Statement: [Schulpforta, locatedIn, Bad Kösen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Kösen Context triple: [Schulpforta, locatedIn, Bad Kösen]
-
A.
Bad Kösen
chosen
Bad Kösen is a spa town in the German state of Saxony-Anhalt, known for its saline springs, historic graduation towers, and scenic location along the Saale River.
-
B.
Bad Köstritz
Bad Köstritz is a small spa town in the German state of Thuringia, best known as the birthplace of composer Heinrich Schütz and for its long-standing brewing tradition.
-
C.
Kötz
Kötz is a municipality in the district of Günzburg in the Bavarian region of Germany.
-
D.
Kozelets
Kozelets is an urban-type settlement in northern Ukraine, historically known as a local administrative and trading center.
-
E.
Kölliken
Kölliken is a municipality in the canton of Aargau in northern Switzerland, known for its residential character and proximity to major transport routes.
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3af45ec8190a32aa4e5f04f6756 |
completed | April 29, 2026, 6:22 a.m. |
Created at: April 17, 2026, 5:33 p.m.