Triple
T9571582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WUN |
E230932
|
entity |
| Predicate | codeFor |
P3746
|
FINISHED |
| Object | Wunsiedel im Fichtelgebirge |
E230926
|
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: Wunsiedel im Fichtelgebirge | Statement: [WUN, codeFor, Wunsiedel im Fichtelgebirge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wunsiedel im Fichtelgebirge Context triple: [WUN, codeFor, Wunsiedel im Fichtelgebirge]
-
A.
Wunsiedel im Fichtelgebirge
chosen
Wunsiedel im Fichtelgebirge is a small Bavarian town in northeastern Germany known for its location in the Fichtel Mountains and its historic town center.
-
B.
Weiler am Berge
Weiler am Berge is a small village that forms one of the districts of the town of Mechernich in North Rhine-Westphalia, Germany.
-
C.
Bad Schussenried
Bad Schussenried is a spa town in southern Germany known for its historic monastery complex and scenic location in Upper Swabia.
-
D.
Waldsassen
Waldsassen is a small town in Bavaria, Germany, known for its historic Cistercian abbey and richly decorated Baroque basilica.
-
E.
Bergrheinfeld
Bergrheinfeld is a municipality in the Schweinfurt district of northern Bavaria, Germany, known for its residential character and proximity to the industrial city of Schweinfurt.
- 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_69ca847f22188190a56e4a97625bef22 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd998bf20881909fad48ecb16dfa31 |
completed | April 1, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1614f33108190901e3037654c50ab |
completed | April 4, 2026, 7:06 p.m. |
Created at: March 30, 2026, 8:04 p.m.