Triple
T9495175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwansen |
E228985
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Kappeln
Kappeln is a small town in northern Germany known for its picturesque harbor on the Schlei inlet and its traditional herring fishery.
|
E802820
|
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: Kappeln | Statement: [Schwansen, hasSettlement, Kappeln]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kappeln Context triple: [Schwansen, hasSettlement, Kappeln]
-
A.
Kapelle
Kapelle is a small municipality and town in the Dutch province of Zeeland, known for its agricultural landscape and historic village character.
-
B.
Kalenberg
Kalenberg is a small waterside village in the Dutch province of Overijssel, known for its canals, reedlands, and traditional houses amid the wetlands of the Weerribben-Wieden area.
-
C.
Kalenberg
Kalenberg is a small district (Ortsteil) of the town of Mechernich in the Euskirchen district of North Rhine-Westphalia, Germany.
-
D.
Kappelrodeck
Kappelrodeck is a municipality in southwestern Germany known for its wine-growing tradition and scenic location at the edge of the Black Forest.
-
E.
Kuppenheim
Kuppenheim is a small town in the Rastatt district of Baden-Württemberg, southwestern Germany, situated near the Black Forest.
- 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: Kappeln Triple: [Schwansen, hasSettlement, Kappeln]
Generated description
Kappeln is a small town in northern Germany known for its picturesque harbor on the Schlei inlet and its traditional herring fishery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kappeln Target entity description: Kappeln is a small town in northern Germany known for its picturesque harbor on the Schlei inlet and its traditional herring fishery.
-
A.
Kapelle
Kapelle is a small municipality and town in the Dutch province of Zeeland, known for its agricultural landscape and historic village character.
-
B.
Kalenberg
Kalenberg is a small waterside village in the Dutch province of Overijssel, known for its canals, reedlands, and traditional houses amid the wetlands of the Weerribben-Wieden area.
-
C.
Kalenberg
Kalenberg is a small district (Ortsteil) of the town of Mechernich in the Euskirchen district of North Rhine-Westphalia, Germany.
-
D.
Kappelrodeck
Kappelrodeck is a municipality in southwestern Germany known for its wine-growing tradition and scenic location at the edge of the Black Forest.
-
E.
Kuppenheim
Kuppenheim is a small town in the Rastatt district of Baden-Württemberg, southwestern Germany, situated near the Black Forest.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ea4a04819092c7842361c6296e |
completed | April 1, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12d34967881909980be6f1be80885 |
completed | April 4, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69d13113474881909201282ce1385073 |
completed | April 4, 2026, 3:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d131ade0588190bdf3cfdbbdd6df8e |
completed | April 4, 2026, 3:43 p.m. |
Created at: March 30, 2026, 7:56 p.m.