Triple
T15053225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eberhard Diepgen |
E379419
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Diepgen
Diepgen is a German surname most notably associated with Eberhard Diepgen, a long-serving former Governing Mayor of Berlin.
|
E1135378
|
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: Diepgen | Statement: [Eberhard Diepgen, familyName, Diepgen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diepgen Context triple: [Eberhard Diepgen, familyName, Diepgen]
-
A.
Subingen
Subingen is a Swiss municipality located in the canton of Solothurn, known for its residential character and proximity to regional transport routes.
-
B.
Oderberg
Oderberg is a small historic town in northeastern Germany near the Oder River, known for its scenic natural surroundings and proximity to the Polish border.
-
C.
Tornesch
Tornesch is a small town in the district of Pinneberg in Schleswig-Holstein, northern Germany, known for its residential character and proximity to Hamburg.
-
D.
Schwansen
Schwansen is a rural peninsula in northern Germany situated between the Schlei inlet and the Eckernförde Bay in the state of Schleswig-Holstein.
-
E.
De Wieden
De Wieden is a renowned wetland nature reserve in the Dutch province of Overijssel, known for its lakes, reed beds, and rich birdlife.
- 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: Diepgen Triple: [Eberhard Diepgen, familyName, Diepgen]
Generated description
Diepgen is a German surname most notably associated with Eberhard Diepgen, a long-serving former Governing Mayor of Berlin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Diepgen Target entity description: Diepgen is a German surname most notably associated with Eberhard Diepgen, a long-serving former Governing Mayor of Berlin.
-
A.
Subingen
Subingen is a Swiss municipality located in the canton of Solothurn, known for its residential character and proximity to regional transport routes.
-
B.
Oderberg
Oderberg is a small historic town in northeastern Germany near the Oder River, known for its scenic natural surroundings and proximity to the Polish border.
-
C.
Tornesch
Tornesch is a small town in the district of Pinneberg in Schleswig-Holstein, northern Germany, known for its residential character and proximity to Hamburg.
-
D.
Schwansen
Schwansen is a rural peninsula in northern Germany situated between the Schlei inlet and the Eckernförde Bay in the state of Schleswig-Holstein.
-
E.
De Wieden
De Wieden is a renowned wetland nature reserve in the Dutch province of Overijssel, known for its lakes, reed beds, and rich birdlife.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda92091c81909180f486edf01405 |
completed | April 15, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5bdeee48190949b0fe63eb6a21a |
completed | May 9, 2026, 3:10 a.m. |
| NEDg | Description generation | batch_69fea79dd1bc8190ae1ac5edad3db9cb |
completed | May 9, 2026, 3:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fea83aaff48190af7a7399e40fdf46 |
completed | May 9, 2026, 3:21 a.m. |
Created at: April 10, 2026, 3:01 a.m.