Triple
T7780929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nienburg |
E221513
|
entity |
| Predicate | hasNameInGerman |
P22792
|
FINISHED |
| Object | Nienburg (Weser) |
E221513
|
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: Nienburg (Weser) | Statement: [Nienburg, hasNameInGerman, Nienburg (Weser)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nienburg (Weser) Context triple: [Nienburg, hasNameInGerman, 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.
Bentheim
Bentheim is a historical county in Lower Saxony, Germany, known for its Reformed Protestant heritage and the former County of Bentheim.
-
E.
Ibbenbüren
Ibbenbüren is a town in North Rhine-Westphalia, Germany, known historically for its coal mining and situated near the Teutoburg Forest.
- 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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69caa4d6cf9881909f5220437db13cc7 |
completed | March 30, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf5c1f20c81908ae2fc35550b91b5 |
completed | March 30, 2026, 10:14 p.m. |
Created at: March 30, 2026, 4:20 p.m.