Triple
T17855250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Peter Wilhelm Beuth |
E445915
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Beuth
Beuth is a German surname most notably associated with Christian Peter Wilhelm Beuth, a 19th-century Prussian statesman and reformer of industry and technology.
|
E1291952
|
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: Beuth | Statement: [Christian Peter Wilhelm Beuth, familyName, Beuth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beuth Context triple: [Christian Peter Wilhelm Beuth, familyName, Beuth]
-
A.
Beuthen
Beuthen is the historical German name for the city of Bytom in southern Poland’s Upper Silesia region.
-
B.
Erasbach
Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
-
C.
Helmbrechts
Helmbrechts is a small town in northern Bavaria, Germany, known for its textile industry and location in the Franconian Forest region.
-
D.
Baar-Ebenhausen
Baar-Ebenhausen is a Bavarian municipality in southern Germany known for its residential character and location along the Ilm River.
-
E.
Veltheim
Veltheim is a former municipality in North Rhine-Westphalia, Germany, that became part of the town of Porta Westfalica through a local government merger.
- 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: Beuth Triple: [Christian Peter Wilhelm Beuth, familyName, Beuth]
Generated description
Beuth is a German surname most notably associated with Christian Peter Wilhelm Beuth, a 19th-century Prussian statesman and reformer of industry and technology.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beuth Target entity description: Beuth is a German surname most notably associated with Christian Peter Wilhelm Beuth, a 19th-century Prussian statesman and reformer of industry and technology.
-
A.
Beuthen
Beuthen is the historical German name for the city of Bytom in southern Poland’s Upper Silesia region.
-
B.
Erasbach
Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
-
C.
Helmbrechts
Helmbrechts is a small town in northern Bavaria, Germany, known for its textile industry and location in the Franconian Forest region.
-
D.
Baar-Ebenhausen
Baar-Ebenhausen is a Bavarian municipality in southern Germany known for its residential character and location along the Ilm River.
-
E.
Veltheim
Veltheim is a former municipality in North Rhine-Westphalia, Germany, that became part of the town of Porta Westfalica through a local government merger.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4978af9b0819091780281344f5352 |
completed | April 19, 2026, 8:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a030c62097c8190a52994d2806cb54a |
completed | May 12, 2026, 11:17 a.m. |
| NEDg | Description generation | batch_6a030d0529f081908d5fd390af9d6bb7 |
completed | May 12, 2026, 11:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a030dbb23208190bb73c4f9cee76f73 |
completed | May 12, 2026, 11:23 a.m. |
Created at: April 10, 2026, 10:17 a.m.