Triple
T22829209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karlsruhe district |
E565749
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Oberderdingen |
—
|
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: Oberderdingen | Statement: [Karlsruhe district, contains, Oberderdingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oberderdingen Context triple: [Karlsruhe district, contains, Oberderdingen]
-
A.
Oberderdingen
chosen
Oberderdingen is a municipality in the district of Karlsruhe in the German state of Baden-Württemberg, known for its winegrowing and picturesque location at the edge of the Kraichgau region.
-
B.
Oberstedten
Oberstedten is a district of the town Oberursel in Hesse, Germany, situated near the Taunus mountain range.
-
C.
Deggendorf
Deggendorf is a town in southeastern Germany situated on the Danube River, known as a regional commercial and transportation hub near the Bavarian Forest.
-
D.
Forchheim
Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
-
E.
Ober-Ramstadt
Ober-Ramstadt is a small town in the German state of Hesse, located southeast of the city of Darmstadt and known for its surrounding forests and residential character.
- 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2a0e308190941064965346f890 |
completed | April 29, 2026, 3:42 a.m. |
Created at: April 17, 2026, 3:34 p.m.