Triple
T6713009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerpen |
E153193
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Brüggen
Brüggen is a locality within the town of Kerpen in North Rhine-Westphalia, Germany.
|
E613493
|
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: Brüggen | Statement: [Kerpen, hasSubdivision, Brüggen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brüggen Context triple: [Kerpen, hasSubdivision, Brüggen]
-
A.
Geldersheim
Geldersheim is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and proximity to the city of Schweinfurt.
-
B.
Bentheim
Bentheim is a historical county in Lower Saxony, Germany, known for its Reformed Protestant heritage and the former County of Bentheim.
-
C.
Nienburg
Nienburg is a historic town in Lower Saxony, Germany, known for its medieval architecture and scenic location along the Weser River.
-
D.
Gailingen
Gailingen is a village in the German municipality of Gailingen am Hochrhein in the state of Baden-Württemberg, near the Swiss border along the High Rhine.
-
E.
Heiligenhaus
Heiligenhaus is a small town in North Rhine-Westphalia, western Germany, known for its manufacturing industry and location between Düsseldorf and Essen.
- 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: Brüggen Triple: [Kerpen, hasSubdivision, Brüggen]
Generated description
Brüggen is a locality within the town of Kerpen in North Rhine-Westphalia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brüggen Target entity description: Brüggen is a locality within the town of Kerpen in North Rhine-Westphalia, Germany.
-
A.
Geldersheim
Geldersheim is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and proximity to the city of Schweinfurt.
-
B.
Bentheim
Bentheim is a historical county in Lower Saxony, Germany, known for its Reformed Protestant heritage and the former County of Bentheim.
-
C.
Nienburg
Nienburg is a historic town in Lower Saxony, Germany, known for its medieval architecture and scenic location along the Weser River.
-
D.
Gailingen
Gailingen is a village in the German municipality of Gailingen am Hochrhein in the state of Baden-Württemberg, near the Swiss border along the High Rhine.
-
E.
Heiligenhaus
Heiligenhaus is a small town in North Rhine-Westphalia, western Germany, known for its manufacturing industry and location between Düsseldorf and Essen.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d121a92c8190a03f384a8aba84da |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c700948788819087f9b466be337286 |
completed | March 27, 2026, 10:11 p.m. |
| NEDg | Description generation | batch_69c703ad7e0c81908da32c96806f3b07 |
completed | March 27, 2026, 10:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7042f23408190b06faafcb3251276 |
completed | March 27, 2026, 10:26 p.m. |
Created at: March 27, 2026, 2:07 p.m.