Triple
T8238671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Kösen |
E192473
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Kurpark |
E706945
|
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: Kurpark | Statement: [Bad Kösen, hasLandmark, Kurpark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kurpark Context triple: [Bad Kösen, hasLandmark, Kurpark]
-
A.
Kurpark
chosen
Kurpark is a historic spa park in Bad Lauchstädt, Germany, known for its landscaped grounds, promenades, and role as a recreational centerpiece of the spa town.
-
B.
Valkhof Park
Valkhof Park is a historic public park in Nijmegen, Netherlands, known for its scenic setting overlooking the Waal River and its proximity to ancient Roman and medieval ruins.
-
C.
U Kleistpark
U Kleistpark is a Berlin U-Bahn station on line U7 located in the Schöneberg district.
-
D.
Seel Park
Seel Park is a football stadium in Mossley, England, serving as the home ground of Mossley A.F.C.
-
E.
Herzogspark
Herzogspark is a historic riverside park in Regensburg, Germany, known for its landscaped gardens, botanical diversity, and scenic views along the Danube.
- 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_69ca82dc8f148190a2c75a98501a7b91 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb783a8cf48190bf85394fd3bd79e2 |
completed | March 31, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3504e6ac8190b4cb12c80a7e7fc0 |
completed | April 1, 2026, 3:08 p.m. |
Created at: March 30, 2026, 5:47 p.m.