Triple
T14926937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sächsische Schweiz-Osterzgebirge |
E372156
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Bannewitz
Bannewitz is a municipality in the Free State of Saxony in eastern Germany, located just south of the city of Dresden.
|
E1171183
|
NE FINISHED |
How this triple was built (4 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: Bannewitz | Statement: [Sächsische Schweiz-Osterzgebirge, containsTown, Bannewitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bannewitz Context triple: [Sächsische Schweiz-Osterzgebirge, containsTown, Bannewitz]
-
A.
Dennewitz
Dennewitz is a village in Brandenburg, Germany, historically notable as the site of a major 1813 battle during the Napoleonic Wars.
-
B.
Zeuthen
Zeuthen is a municipality in Brandenburg, Germany, known for hosting a major campus of the DESY particle physics research center.
-
C.
Seelitz
Seelitz is a municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the Mittelsachsen region.
-
D.
Beelitz
Beelitz is a small German town in the state of Brandenburg, best known for its historic asparagus cultivation and the nearby Beelitz-Heilstätten sanatorium complex.
-
E.
Gröditz
Gröditz is a small industrial town in the German state of Saxony, known historically for its steel production.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bannewitz Triple: [Sächsische Schweiz-Osterzgebirge, containsTown, Bannewitz]
Generated description
Bannewitz is a municipality in the Free State of Saxony in eastern Germany, located just south of the city of Dresden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bannewitz Target entity description: Bannewitz is a municipality in the Free State of Saxony in eastern Germany, located just south of the city of Dresden.
-
A.
Dennewitz
Dennewitz is a village in Brandenburg, Germany, historically notable as the site of a major 1813 battle during the Napoleonic Wars.
-
B.
Zeuthen
Zeuthen is a municipality in Brandenburg, Germany, known for hosting a major campus of the DESY particle physics research center.
-
C.
Seelitz
Seelitz is a municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the Mittelsachsen region.
-
D.
Beelitz
Beelitz is a small German town in the state of Brandenburg, best known for its historic asparagus cultivation and the nearby Beelitz-Heilstätten sanatorium complex.
-
E.
Gröditz
Gröditz is a small industrial town in the German state of Saxony, known historically for its steel production.
- F. None of above. chosen
Provenance (5 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded633da0c8190b39f606212e48e71 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ec12de8819097cd83530e54f54b |
completed | May 9, 2026, 5:28 p.m. |
| NEDg | Description generation | batch_69ff6f691b1c8190a5b6ede22f90a1d9 |
completed | May 9, 2026, 5:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff700c8c748190a24996936d591435 |
completed | May 9, 2026, 5:34 p.m. |
Created at: April 10, 2026, 2:35 a.m.