Triple
T3690681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberhavel |
E78334
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Birkenwerder
Birkenwerder is a small municipality in the German state of Brandenburg, located just north of Berlin and known for its residential character and surrounding forests.
|
E402028
|
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: Birkenwerder | Statement: [Oberhavel, hasMunicipality, Birkenwerder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Birkenwerder Context triple: [Oberhavel, hasMunicipality, Birkenwerder]
-
A.
Friedrichsruh
Friedrichsruh is a small village in northern Germany best known as the estate and final residence of statesman Otto von Bismarck.
-
B.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
C.
Grevesmühlen
Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
-
D.
Hohenfinow
Hohenfinow is a small municipality in the Barnim district of the federal state of Brandenburg in northeastern Germany.
-
E.
Heringsdorf
Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
- 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: Birkenwerder Triple: [Oberhavel, hasMunicipality, Birkenwerder]
Generated description
Birkenwerder is a small municipality in the German state of Brandenburg, located just north of Berlin and known for its residential character and surrounding forests.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Birkenwerder Target entity description: Birkenwerder is a small municipality in the German state of Brandenburg, located just north of Berlin and known for its residential character and surrounding forests.
-
A.
Friedrichsruh
Friedrichsruh is a small village in northern Germany best known as the estate and final residence of statesman Otto von Bismarck.
-
B.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
C.
Grevesmühlen
Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
-
D.
Hohenfinow
Hohenfinow is a small municipality in the Barnim district of the federal state of Brandenburg in northeastern Germany.
-
E.
Heringsdorf
Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
- 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_69ad85e285a081908f8cbfa9e2ed9b75 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4e6147c8190ae358e8cc94f479c |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b53367ad5c81909f7bcbbc967514b7 |
completed | March 14, 2026, 10:07 a.m. |
| NEDg | Description generation | batch_69b534e575408190bfb87729d12f0ca7 |
completed | March 14, 2026, 10:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b53557089481908bd2a08f4b018c7e |
completed | March 14, 2026, 10:15 a.m. |
Created at: March 8, 2026, 3:26 p.m.