Triple
T8657965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyffhäuserkreis |
E205469
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Greußen
Greußen is a small town in the Kyffhäuserkreis district of Thuringia in central Germany, known for its rural character and regional historical heritage.
|
E752343
|
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: Greußen | Statement: [Kyffhäuserkreis, contains, Greußen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greußen Context triple: [Kyffhäuserkreis, contains, Greußen]
-
A.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
B.
Brieg
Brieg is a historic town in southwestern Poland, known today as Brzeg, that was formerly part of Germany’s Silesia region.
-
C.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
D.
Haslach
Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
-
E.
Haslach
Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
- 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: Greußen Triple: [Kyffhäuserkreis, contains, Greußen]
Generated description
Greußen is a small town in the Kyffhäuserkreis district of Thuringia in central Germany, known for its rural character and regional historical heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Greußen Target entity description: Greußen is a small town in the Kyffhäuserkreis district of Thuringia in central Germany, known for its rural character and regional historical heritage.
-
A.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
B.
Brieg
Brieg is a historic town in southwestern Poland, known today as Brzeg, that was formerly part of Germany’s Silesia region.
-
C.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
D.
Haslach
Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
-
E.
Haslach
Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc486d576081908ad28749c7971432 |
completed | March 31, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf285de8c081908abca2189f206a40 |
completed | April 3, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_69cf2bcff84881908a7985fdf8189583 |
completed | April 3, 2026, 2:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf2ca1ddac8190a36367e6bba8e3c8 |
completed | April 3, 2026, 2:57 a.m. |
Created at: March 30, 2026, 6:30 p.m.