Triple
T15687447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fürstenberg/Havel |
E380238
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Bredereiche
Bredereiche is a small district within the town of Fürstenberg/Havel in the state of Brandenburg, Germany.
|
E1171523
|
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: Bredereiche | Statement: [Fürstenberg/Havel, hasSubdivision, Bredereiche]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bredereiche Context triple: [Fürstenberg/Havel, hasSubdivision, Bredereiche]
-
A.
Flachsland
Flachsland is a German-language surname associated with individuals such as Maria Karoline Flachsland.
-
B.
Veldidena
Veldidena was a significant Roman-era settlement and strategic center located in the province of Raetia, in the region of present-day Austria.
-
C.
Kamperland
Kamperland is a village in the Dutch province of Zeeland, located on the island of Noord-Beveland and known as a coastal and recreational destination.
-
D.
Landsmeer
Landsmeer is a small Dutch town and municipality in North Holland, situated just north of Amsterdam and known for its watery landscapes and nature reserves.
-
E.
Maasland
Maasland is a historical region in the Low Countries centered along the river Meuse, known for its medieval political and cultural significance.
- 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: Bredereiche Triple: [Fürstenberg/Havel, hasSubdivision, Bredereiche]
Generated description
Bredereiche is a small district within the town of Fürstenberg/Havel in the state of Brandenburg, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bredereiche Target entity description: Bredereiche is a small district within the town of Fürstenberg/Havel in the state of Brandenburg, Germany.
-
A.
Flachsland
Flachsland is a German-language surname associated with individuals such as Maria Karoline Flachsland.
-
B.
Veldidena
Veldidena was a significant Roman-era settlement and strategic center located in the province of Raetia, in the region of present-day Austria.
-
C.
Kamperland
Kamperland is a village in the Dutch province of Zeeland, located on the island of Noord-Beveland and known as a coastal and recreational destination.
-
D.
Landsmeer
Landsmeer is a small Dutch town and municipality in North Holland, situated just north of Amsterdam and known for its watery landscapes and nature reserves.
-
E.
Maasland
Maasland is a historical region in the Low Countries centered along the river Meuse, known for its medieval political and cultural significance.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4cee5481908699fbb2b7bdd2f6 |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ee91340819086c8f51e8eb477aa |
completed | May 9, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69ff6fd9c968819098b2552a9deb0445 |
completed | May 9, 2026, 5:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff708d42448190a53b90e00721eaa5 |
completed | May 9, 2026, 5:36 p.m. |
Created at: April 10, 2026, 4:44 a.m.