Triple
T3181092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isar |
E66587
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Bad Tölz |
E10394
|
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 Tölz | Statement: [Isar, flowsThrough, Bad Tölz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Tölz Context triple: [Isar, flowsThrough, Bad Tölz]
-
A.
Bad Tölz
chosen
Bad Tölz is a Bavarian spa town in southern Germany known for its historic old town, alpine scenery, and traditional German architecture.
-
B.
Bad Mergentheim
Bad Mergentheim is a historic spa town in the German state of Baden-Württemberg, renowned for its mineral springs and picturesque setting in the Tauber Valley.
-
C.
Bad Tölz-Wolfratshausen
Bad Tölz-Wolfratshausen is a rural district in Upper Bavaria, Germany, known for its picturesque Alpine foothills, spa towns, and traditional Bavarian culture.
-
D.
Bad Lauchstädt
Bad Lauchstädt is a historic spa town in the German state of Saxony-Anhalt, known for its classical Kurpark and Goethe-Theater.
-
E.
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.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6a1280c8190b59a2afd30312c02 |
completed | March 8, 2026, 4:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235fd1688819080fa1d73d2b233ba |
completed | March 12, 2026, 3:41 a.m. |
Created at: March 8, 2026, 3:06 p.m.