Triple
T17820520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fichtelgebirge |
E444968
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Wunsiedel |
—
|
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: Wunsiedel | Statement: [Fichtelgebirge, nearbyCity, Wunsiedel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wunsiedel Context triple: [Fichtelgebirge, nearbyCity, Wunsiedel]
-
A.
Wunsiedel
chosen
Wunsiedel is a historic town in northeastern Bavaria, Germany, known for its location in the Fichtel Mountains and its traditional Franconian architecture.
-
B.
Odelzhausen
Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
-
C.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
D.
Neusäß
Neusäß is a town in Bavaria, Germany, located just northwest of the city of Augsburg and functioning largely as a residential and commuter suburb.
-
E.
Geretsried
Geretsried is a town in Upper Bavaria, Germany, situated on the Isar River and known as the largest town in the Bad Tölz-Wolfratshausen district.
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48910eb8881908db8ec08e2752d7d |
completed | April 19, 2026, 7:49 a.m. |
Created at: April 10, 2026, 10:15 a.m.