Triple
T21166695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rotenburg an der Fulda |
E521581
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Zell an der Mosel |
—
|
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: Zell an der Mosel | Statement: [Rotenburg an der Fulda, hasTwinTown, Zell an der Mosel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zell an der Mosel Context triple: [Rotenburg an der Fulda, hasTwinTown, Zell an der Mosel]
-
A.
Zell an der Mosel
chosen
Zell an der Mosel is a small wine-producing town on the Moselle River in Rhineland-Palatinate, western Germany.
-
B.
Monschau
Monschau is a historic small town in western Germany’s Eifel region, known for its well-preserved half-timbered houses, medieval center, and scenic setting along the Rur River.
-
C.
Odelzhausen
Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
-
D.
Sulzheim
Sulzheim is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
E.
Nussloch
Nussloch is a small town in southwestern Germany, known in part for hosting the headquarters of medical technology company Leica Biosystems.
- 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7270fce708190a5715b55b406dd4e |
completed | April 21, 2026, 7:28 a.m. |
Created at: April 16, 2026, 2:59 p.m.