Triple
T20849496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B 3 |
E513317
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Nienburg/Weser |
—
|
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: Nienburg/Weser | Statement: [B 3, connects, Nienburg/Weser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nienburg/Weser Context triple: [B 3, connects, Nienburg/Weser]
-
A.
Nienburg
chosen
Nienburg is a historic town in Lower Saxony, Germany, known for its medieval architecture and scenic location along the Weser River.
-
B.
Nienburg (Saale)
Nienburg (Saale) is a small town in the Saxony-Anhalt region of Germany, known for its location at the confluence of the Saale and Bode rivers and its historic medieval architecture.
-
C.
Northeim
Northeim is a town in Lower Saxony, Germany, known for its medieval old town and location in the Leine River valley.
-
D.
Meppen
Meppen is a historic town in Lower Saxony, Germany, known as a regional center in the Emsland district near the Dutch border.
-
E.
Lüneburg
Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3520b0081908ce0f43e8f20b24c |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:43 p.m.