Triple
T10215698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havelland |
E242434
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Mühlenberge
Mühlenberge is a small rural municipality in the Havelland district of the German state of Brandenburg.
|
E850654
|
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: Mühlenberge | Statement: [Havelland, containsMunicipality, Mühlenberge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mühlenberge Context triple: [Havelland, containsMunicipality, Mühlenberge]
-
A.
Bodenmais
Bodenmais is a Bavarian spa and holiday resort town in the Bavarian Forest of Germany, known for its glassmaking tradition and outdoor recreation.
-
B.
Giebichenstein
Giebichenstein is a district of Halle (Saale) in Germany, historically notable as the birthplace of World War I flying ace Oswald Boelcke.
-
C.
Wingsbach
Wingsbach is a small district within the town of Taunusstein in the Rheingau-Taunus region of Hesse, Germany.
-
D.
Steigerwald
Steigerwald is a forested hill range and nature area in northern Bavaria, Germany, known for its beech forests, vineyards, and traditional Franconian landscapes.
-
E.
Hohne
Hohne is a village in Lower Saxony, Germany, historically notable for its military garrison and association with British Army units.
- 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: Mühlenberge Triple: [Havelland, containsMunicipality, Mühlenberge]
Generated description
Mühlenberge is a small rural municipality in the Havelland district of the German state of Brandenburg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mühlenberge Target entity description: Mühlenberge is a small rural municipality in the Havelland district of the German state of Brandenburg.
-
A.
Bodenmais
Bodenmais is a Bavarian spa and holiday resort town in the Bavarian Forest of Germany, known for its glassmaking tradition and outdoor recreation.
-
B.
Giebichenstein
Giebichenstein is a district of Halle (Saale) in Germany, historically notable as the birthplace of World War I flying ace Oswald Boelcke.
-
C.
Wingsbach
Wingsbach is a small district within the town of Taunusstein in the Rheingau-Taunus region of Hesse, Germany.
-
D.
Steigerwald
Steigerwald is a forested hill range and nature area in northern Bavaria, Germany, known for its beech forests, vineyards, and traditional Franconian landscapes.
-
E.
Hohne
Hohne is a village in Lower Saxony, Germany, historically notable for its military garrison and association with British Army units.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa2894d0819095704449ecc2db6c |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a804e8748190b4ebcfa9a0bb889f |
completed | April 8, 2026, 7:09 p.m. |
| NEDg | Description generation | batch_69d6d0003434819093e3f82a556db79c |
completed | April 8, 2026, 10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6df3c8f748190923db41ef1a9a03a |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 6, 2026, 11:05 a.m.