Triple
T1711539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Düsseldorf |
E36993
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Oberkassel
Oberkassel is a riverside district of Düsseldorf in western Germany, known for its affluent residential areas and scenic location along the Rhine.
|
E201502
|
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: Oberkassel | Statement: [Düsseldorf, hasDistrict, Oberkassel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oberkassel Context triple: [Düsseldorf, hasDistrict, Oberkassel]
-
A.
Seubelsdorf
Seubelsdorf is a village that forms one of the local subdivisions of the town of Lichtenfels in Bavaria, Germany.
-
B.
Sachsenhausen
Sachsenhausen is a historic and culturally vibrant district of Frankfurt am Main, known for its traditional apple wine taverns, museums, and picturesque old town streets.
-
C.
Ronsdorf
Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
-
D.
Langendorf
Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
-
E.
Alt-Mariendorf
Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
- 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: Oberkassel Triple: [Düsseldorf, hasDistrict, Oberkassel]
Generated description
Oberkassel is a riverside district of Düsseldorf in western Germany, known for its affluent residential areas and scenic location along the Rhine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oberkassel Target entity description: Oberkassel is a riverside district of Düsseldorf in western Germany, known for its affluent residential areas and scenic location along the Rhine.
-
A.
Seubelsdorf
Seubelsdorf is a village that forms one of the local subdivisions of the town of Lichtenfels in Bavaria, Germany.
-
B.
Sachsenhausen
Sachsenhausen is a historic and culturally vibrant district of Frankfurt am Main, known for its traditional apple wine taverns, museums, and picturesque old town streets.
-
C.
Ronsdorf
Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
-
D.
Langendorf
Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
-
E.
Alt-Mariendorf
Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
- 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_69a88617439c819094ffb5d16a0f6307 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa63149288819082e7055d0d292d1d |
completed | March 6, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5be1a2c819083b95d55c969b9d6 |
completed | March 8, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69adb8b3c0a48190bf5f3a32d8862c54 |
completed | March 8, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb97b8c8081909a806d16efd5882b |
completed | March 8, 2026, 6:01 p.m. |
Created at: March 4, 2026, 7:30 p.m.