Triple
T13351706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Behmen von Bleibruck |
E318084
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
von Bleibruck
Von Bleibruck is a German-language noble surname historically associated with Central European aristocratic lineages.
|
E1034755
|
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 Bleibruck | Statement: [Behmen von Bleibruck, familyName, von Bleibruck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: von Bleibruck Context triple: [Behmen von Bleibruck, familyName, von Bleibruck]
-
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 Broich
Von Broich is a German noble family name historically associated with military officers and aristocracy.
-
C.
von Kühn
von Kühn is a German noble family name historically associated with figures such as Sophie von Kühn.
-
D.
von Sonnenthal
Von Sonnenthal is a German-language surname historically associated with notable figures in Central European theater and culture.
-
E.
von Weichs
von Weichs is a German noble family name most prominently associated with Maximilian von Weichs, a senior Wehrmacht field marshal during World War II.
- 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 Bleibruck Triple: [Behmen von Bleibruck, familyName, von Bleibruck]
Generated description
Von Bleibruck is a German-language noble surname historically associated with Central European aristocratic lineages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: von Bleibruck Target entity description: Von Bleibruck is a German-language noble surname historically associated with Central European aristocratic lineages.
-
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 Broich
Von Broich is a German noble family name historically associated with military officers and aristocracy.
-
C.
von Kühn
von Kühn is a German noble family name historically associated with figures such as Sophie von Kühn.
-
D.
von Sonnenthal
Von Sonnenthal is a German-language surname historically associated with notable figures in Central European theater and culture.
-
E.
von Weichs
von Weichs is a German noble family name most prominently associated with Maximilian von Weichs, a senior Wehrmacht field marshal during World War II.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f47fd7c8190b8d98a181acd7710 |
completed | May 3, 2026, 10:11 a.m. |
| NEDg | Description generation | batch_69f7204b6f108190bca6a0140620e03e |
completed | May 3, 2026, 10:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f720fbf0bc81908c68cf2844938e45 |
completed | May 3, 2026, 10:18 a.m. |
Created at: April 9, 2026, 9:32 p.m.