Triple
T13621898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juergen Weigert |
E325476
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Weigert
Weigert is a German-language surname borne by various notable individuals in fields such as science, sports, and the arts.
|
E1050232
|
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: Weigert | Statement: [Juergen Weigert, familyName, Weigert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weigert Context triple: [Juergen Weigert, familyName, Weigert]
-
A.
Lehwaldt
Lehwaldt was a Prussian field marshal best known for commanding Prussian forces in the early campaigns of the Seven Years' War in Europe.
-
B.
Stahlecker
Stahlecker is a German-language surname most notably associated with Franz Walter Stahlecker, a high-ranking SS officer and Nazi official during World War II.
-
C.
Otzberg
Otzberg is a small municipality in the German state of Hesse, known for its historic Veste Otzberg hilltop castle and rural surroundings.
-
D.
Trichardt
Trichardt is a small town in Mpumalanga, South Africa, known for its close association with the nearby industrial and coal-mining hub of Secunda.
-
E.
Kniphausen
Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
- 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: Weigert Triple: [Juergen Weigert, familyName, Weigert]
Generated description
Weigert is a German-language surname borne by various notable individuals in fields such as science, sports, and the arts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weigert Target entity description: Weigert is a German-language surname borne by various notable individuals in fields such as science, sports, and the arts.
-
A.
Lehwaldt
Lehwaldt was a Prussian field marshal best known for commanding Prussian forces in the early campaigns of the Seven Years' War in Europe.
-
B.
Stahlecker
Stahlecker is a German-language surname most notably associated with Franz Walter Stahlecker, a high-ranking SS officer and Nazi official during World War II.
-
C.
Otzberg
Otzberg is a small municipality in the German state of Hesse, known for its historic Veste Otzberg hilltop castle and rural surroundings.
-
D.
Trichardt
Trichardt is a small town in Mpumalanga, South Africa, known for its close association with the nearby industrial and coal-mining hub of Secunda.
-
E.
Kniphausen
Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0b0c9008190836242da2d6a8cbe |
completed | April 12, 2026, 2:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77fa291f48190a0ee7a228ea303bc |
completed | May 3, 2026, 5:02 p.m. |
| NEDg | Description generation | batch_69f780a8f3fc8190b3fce40e2de318af |
completed | May 3, 2026, 5:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7812aa15081909793181722f9d442 |
completed | May 3, 2026, 5:08 p.m. |
Created at: April 9, 2026, 9:50 p.m.