Triple
T13808953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte von Lengefeld |
E331832
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
von Lengefeld
von Lengefeld is a German noble family name historically associated with figures in Weimar literary circles.
|
E1062814
|
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 Lengefeld | Statement: [Charlotte von Lengefeld, familyName, von Lengefeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: von Lengefeld Context triple: [Charlotte von Lengefeld, familyName, von Lengefeld]
-
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.
von Falkenhausen
Von Falkenhausen is a German noble family name historically associated with military and administrative figures in Prussia and the German Empire.
-
C.
von Lichnowsky
von Lichnowsky is the surname of a prominent Silesian noble family of princes known for their influence in Prussian and Austrian political and cultural life.
-
D.
von Schlieben
von Schlieben is a German noble family name historically associated with military officers and aristocracy.
-
E.
Langerfeld
Langerfeld is a district of the German city of Wuppertal, located in the state of North Rhine-Westphalia.
- 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 Lengefeld Triple: [Charlotte von Lengefeld, familyName, von Lengefeld]
Generated description
von Lengefeld is a German noble family name historically associated with figures in Weimar literary circles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: von Lengefeld Target entity description: von Lengefeld is a German noble family name historically associated with figures in Weimar literary circles.
-
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.
von Falkenhausen
Von Falkenhausen is a German noble family name historically associated with military and administrative figures in Prussia and the German Empire.
-
C.
von Lichnowsky
von Lichnowsky is the surname of a prominent Silesian noble family of princes known for their influence in Prussian and Austrian political and cultural life.
-
D.
von Schlieben
von Schlieben is a German noble family name historically associated with military officers and aristocracy.
-
E.
Langerfeld
Langerfeld is a district of the German city of Wuppertal, located in the state of North Rhine-Westphalia.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026eae8481908b8880635e6a9152 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b08fbc348190a199c5d92e0e46be |
completed | May 3, 2026, 8:31 p.m. |
| NEDg | Description generation | batch_69f7b15143108190a49a09afba93eb45 |
completed | May 3, 2026, 8:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7b50c31ac81909b17013d57dda164 |
completed | May 3, 2026, 8:50 p.m. |
Created at: April 9, 2026, 10:12 p.m.