Triple
T21947611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Spa Towns of Europe |
E541973
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Bad Pyrmont |
—
|
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 Pyrmont | Statement: [Great Spa Towns of Europe, hasPart, Bad Pyrmont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Pyrmont Context triple: [Great Spa Towns of Europe, hasPart, Bad Pyrmont]
-
A.
Bad Pyrmont
chosen
Bad Pyrmont is a German spa town in Lower Saxony renowned for its mineral springs, historic Kurpark, and long tradition as a health resort.
-
B.
Bad Harzburg
Bad Harzburg is a German spa and resort town on the northern edge of the Harz Mountains, known for its thermal baths, hiking trails, and historic castle ruins.
-
C.
Bad Heilbrunn
Bad Heilbrunn is a spa municipality in Upper Bavaria, Germany, known for its health resorts and scenic Alpine foothills setting.
-
D.
Bad Grönenbach
Bad Grönenbach is a spa town in the Bavarian Allgäu region of southern Germany, known for its health resorts and picturesque rural surroundings.
-
E.
Bad Vilbel
Bad Vilbel is a spa town in the German state of Hesse, known for its mineral springs and proximity to Frankfurt am Main.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243a2f788190bd4625fa79888696 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:57 p.m.