Triple
T10587220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kulmbach district |
E249884
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Ludwigschorgast
Ludwigschorgast is a small municipality in the Bavarian region of Germany, known for its rural character and location within the Franconian landscape.
|
E879883
|
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: Ludwigschorgast | Statement: [Kulmbach district, hasMunicipality, Ludwigschorgast]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludwigschorgast Context triple: [Kulmbach district, hasMunicipality, Ludwigschorgast]
-
A.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
B.
Suhrendorf
Suhrendorf is a small coastal village on the German Baltic Sea island of Ummanz, known for its rural charm and proximity to nature and water sports areas.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
E.
Stühlingen
Stühlingen is a small town in the state of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its scenic setting in the Black Forest region.
- 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: Ludwigschorgast Triple: [Kulmbach district, hasMunicipality, Ludwigschorgast]
Generated description
Ludwigschorgast is a small municipality in the Bavarian region of Germany, known for its rural character and location within the Franconian landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ludwigschorgast Target entity description: Ludwigschorgast is a small municipality in the Bavarian region of Germany, known for its rural character and location within the Franconian landscape.
-
A.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
B.
Suhrendorf
Suhrendorf is a small coastal village on the German Baltic Sea island of Ummanz, known for its rural charm and proximity to nature and water sports areas.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
E.
Stühlingen
Stühlingen is a small town in the state of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its scenic setting in the Black Forest region.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5276b0ae48190b2935230363239e0 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9988fca088190b13b651985677a6a |
completed | April 11, 2026, 12:40 a.m. |
| NEDg | Description generation | batch_69d99e8312188190bec3090f34a7b9b9 |
completed | April 11, 2026, 1:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d99f50e0888190b8e7b2547e1526af |
completed | April 11, 2026, 1:09 a.m. |
Created at: April 6, 2026, 12:39 p.m.