Triple
T15250644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meissen district |
E364508
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Klipphausen
Klipphausen is a municipality in the Free State of Saxony in eastern Germany, known for its rural landscape, historic estates, and proximity to the city of Dresden.
|
E1187201
|
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: Klipphausen | Statement: [Meissen district, containsMunicipality, Klipphausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klipphausen Context triple: [Meissen district, containsMunicipality, Klipphausen]
-
A.
Kaufering
Kaufering is a municipality in Bavaria, Germany, known historically for its World War II subcamps of Dachau and its location near the town of Landsberg am Lech.
-
B.
Aulhausen
Aulhausen is a district of the town Rüdesheim am Rhein in the Rheingau region of Hesse, Germany, known for its scenic vineyards and rural character.
-
C.
Schaafheim
Schaafheim is a municipality in the state of Hesse in central Germany.
-
D.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
E.
Babenhausen
Babenhausen is a small town in the German state of Hesse, known for its historic old town and location southeast of Frankfurt am Main.
- 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: Klipphausen Triple: [Meissen district, containsMunicipality, Klipphausen]
Generated description
Klipphausen is a municipality in the Free State of Saxony in eastern Germany, known for its rural landscape, historic estates, and proximity to the city of Dresden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Klipphausen Target entity description: Klipphausen is a municipality in the Free State of Saxony in eastern Germany, known for its rural landscape, historic estates, and proximity to the city of Dresden.
-
A.
Kaufering
Kaufering is a municipality in Bavaria, Germany, known historically for its World War II subcamps of Dachau and its location near the town of Landsberg am Lech.
-
B.
Aulhausen
Aulhausen is a district of the town Rüdesheim am Rhein in the Rheingau region of Hesse, Germany, known for its scenic vineyards and rural character.
-
C.
Schaafheim
Schaafheim is a municipality in the state of Hesse in central Germany.
-
D.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
E.
Babenhausen
Babenhausen is a small town in the German state of Hesse, known for its historic old town and location southeast of Frankfurt am Main.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f62b9c8190b9ad40e2d1912b63 |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3aeb59c8190a39ccb4df7815ed0 |
completed | May 9, 2026, 11:30 p.m. |
| NEDg | Description generation | batch_69ffc47bce748190a651fff307aad88d |
completed | May 9, 2026, 11:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc4e14e1881909210a78426546e88 |
completed | May 9, 2026, 11:36 p.m. |
Created at: April 10, 2026, 3:13 a.m.