Triple
T3690691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberhavel |
E78334
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Löwenberger Land
Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
|
E384208
|
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: Löwenberger Land | Statement: [Oberhavel, hasMunicipality, Löwenberger Land]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Löwenberger Land Context triple: [Oberhavel, hasMunicipality, Löwenberger Land]
-
A.
Rübeland
Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
-
B.
Mühlenbecker Land
Mühlenbecker Land is a municipality in the Oberhavel district of Brandenburg, Germany, known for its proximity to Berlin and its mix of forests, lakes, and residential areas.
-
C.
Kellerwald
Kellerwald is a low mountain forest region in central Germany known for its ancient beech woodlands and protected national park status.
-
D.
Flachsland
Flachsland is a German-language surname associated with individuals such as Maria Karoline Flachsland.
-
E.
Badenburg
Badenburg is an ornate pavilion within Munich’s Nymphenburg Palace park, known for its richly decorated interiors and historical bathing hall.
- 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: Löwenberger Land Triple: [Oberhavel, hasMunicipality, Löwenberger Land]
Generated description
Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Löwenberger Land Target entity description: Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
-
A.
Rübeland
Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
-
B.
Mühlenbecker Land
Mühlenbecker Land is a municipality in the Oberhavel district of Brandenburg, Germany, known for its proximity to Berlin and its mix of forests, lakes, and residential areas.
-
C.
Kellerwald
Kellerwald is a low mountain forest region in central Germany known for its ancient beech woodlands and protected national park status.
-
D.
Flachsland
Flachsland is a German-language surname associated with individuals such as Maria Karoline Flachsland.
-
E.
Badenburg
Badenburg is an ornate pavilion within Munich’s Nymphenburg Palace park, known for its richly decorated interiors and historical bathing hall.
- 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_69b4db01e118819090438d80898cf73b |
completed | March 14, 2026, 3:50 a.m. |
| NEDg | Description generation | batch_69b4dbd0b6e88190a857afe3c1041788 |
completed | March 14, 2026, 3:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4dc5114ec8190aee92e21a48ae268 |
completed | March 14, 2026, 3:56 a.m. |
Created at: March 8, 2026, 3:26 p.m.