Triple
T14333879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potsdam-Mittelmark |
E355420
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Wiesenburg/Mark
Wiesenburg/Mark is a small municipality in the German state of Brandenburg, known for its historic castle and extensive parkland.
|
E1094011
|
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: Wiesenburg/Mark | Statement: [Potsdam-Mittelmark, containsTown, Wiesenburg/Mark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wiesenburg/Mark Context triple: [Potsdam-Mittelmark, containsTown, Wiesenburg/Mark]
-
A.
Witzenhausen
Witzenhausen is a small town in northern Hesse, Germany, known for its cherry orchards and agricultural research institutions.
-
B.
Willingshausen
Willingshausen is a small municipality in central Germany known for its historic artists’ colony and rural cultural heritage.
-
C.
Wülscheid
Wülscheid is a small locality within the Aegidienberg district of Bad Honnef in North Rhine-Westphalia, Germany.
-
D.
Ibbenbüren
Ibbenbüren is a town in North Rhine-Westphalia, Germany, known historically for its coal mining and situated near the Teutoburg Forest.
-
E.
Wörsbach
Wörsbach is a small river in Hesse, Germany, that forms part of the local drainage system for the Idsteiner Senke basin.
- 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: Wiesenburg/Mark Triple: [Potsdam-Mittelmark, containsTown, Wiesenburg/Mark]
Generated description
Wiesenburg/Mark is a small municipality in the German state of Brandenburg, known for its historic castle and extensive parkland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wiesenburg/Mark Target entity description: Wiesenburg/Mark is a small municipality in the German state of Brandenburg, known for its historic castle and extensive parkland.
-
A.
Witzenhausen
Witzenhausen is a small town in northern Hesse, Germany, known for its cherry orchards and agricultural research institutions.
-
B.
Willingshausen
Willingshausen is a small municipality in central Germany known for its historic artists’ colony and rural cultural heritage.
-
C.
Wülscheid
Wülscheid is a small locality within the Aegidienberg district of Bad Honnef in North Rhine-Westphalia, Germany.
-
D.
Ibbenbüren
Ibbenbüren is a town in North Rhine-Westphalia, Germany, known historically for its coal mining and situated near the Teutoburg Forest.
-
E.
Wörsbach
Wörsbach is a small river in Hesse, Germany, that forms part of the local drainage system for the Idsteiner Senke basin.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c20d2148190bb534bef338e871d |
completed | April 14, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd469634688190980df59ee482b792 |
completed | May 8, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69fd47e2b8d481909ed8274a96615b36 |
completed | May 8, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4879b2688190ac208545ae226c93 |
completed | May 8, 2026, 2:20 a.m. |
Created at: April 10, 2026, 1:13 a.m.