Triple
T10326474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl-Wilhelm von Schlieben |
E242775
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
von Schlieben
von Schlieben is a German noble family name historically associated with military officers and aristocracy.
|
E855522
|
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: von Schlieben | Statement: [Karl-Wilhelm von Schlieben, familyName, von Schlieben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: von Schlieben Context triple: [Karl-Wilhelm von Schlieben, familyName, von Schlieben]
-
A.
von Schlebrügge
von Schlebrügge is the aristocratic German-Swedish family name of Nena von Schlebrügge, a former fashion model and mother of actress Uma Thurman.
-
B.
Seelitz
Seelitz is a municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the Mittelsachsen region.
-
C.
Löhr
Löhr is a German-language surname borne by various notable individuals, including figures in military, arts, and public life.
-
D.
Wittlich
Wittlich is a small town in the Rhineland-Palatinate region of western Germany, known for its wine production and historic old town.
-
E.
Schillig
Schillig is a small coastal resort village in northern Germany known for its sandy North Sea beaches and proximity to the Wadden Sea mudflats.
- 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: von Schlieben Triple: [Karl-Wilhelm von Schlieben, familyName, von Schlieben]
Generated description
von Schlieben is a German noble family name historically associated with military officers and aristocracy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: von Schlieben Target entity description: von Schlieben is a German noble family name historically associated with military officers and aristocracy.
-
A.
von Schlebrügge
von Schlebrügge is the aristocratic German-Swedish family name of Nena von Schlebrügge, a former fashion model and mother of actress Uma Thurman.
-
B.
Seelitz
Seelitz is a municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the Mittelsachsen region.
-
C.
Löhr
Löhr is a German-language surname borne by various notable individuals, including figures in military, arts, and public life.
-
D.
Wittlich
Wittlich is a small town in the Rhineland-Palatinate region of western Germany, known for its wine production and historic old town.
-
E.
Schillig
Schillig is a small coastal resort village in northern Germany known for its sandy North Sea beaches and proximity to the Wadden Sea mudflats.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ce69b881909f27d97c90643634 |
completed | April 7, 2026, 10:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71dafa9308190ae0d3c34ba0c58b1 |
completed | April 9, 2026, 3:31 a.m. |
| NEDg | Description generation | batch_69d731887d2081908e6b4e33d400582f |
completed | April 9, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7329189708190bbd21bd40ec029b0 |
completed | April 9, 2026, 5:01 a.m. |
Created at: April 6, 2026, 11:51 a.m.