Triple
T13754626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donau-Ries |
E330443
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Bissingen
Bissingen is a municipality in the Donau-Ries district of Bavaria in southern Germany, known for its rural character and location near the Swabian Jura.
|
E1122816
|
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: Bissingen | Statement: [Donau-Ries, containsMunicipality, Bissingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bissingen Context triple: [Donau-Ries, containsMunicipality, Bissingen]
-
A.
Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
B.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
C.
Effingen
Effingen is a small Swiss village and former municipality in the canton of Aargau, known for its rural character and location near the Jura Mountains.
-
D.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
E.
Merzhausen
Merzhausen is a village-level district that forms one of the subdivisions of the town of Usingen in the Hochtaunus region of Hesse, Germany.
- 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: Bissingen Triple: [Donau-Ries, containsMunicipality, Bissingen]
Generated description
Bissingen is a municipality in the Donau-Ries district of Bavaria in southern Germany, known for its rural character and location near the Swabian Jura.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bissingen Target entity description: Bissingen is a municipality in the Donau-Ries district of Bavaria in southern Germany, known for its rural character and location near the Swabian Jura.
-
A.
Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
B.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
C.
Effingen
Effingen is a small Swiss village and former municipality in the canton of Aargau, known for its rural character and location near the Jura Mountains.
-
D.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
E.
Merzhausen
Merzhausen is a village-level district that forms one of the subdivisions of the town of Usingen in the Hochtaunus region of Hesse, Germany.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02179c948190a652cc8c586e418f |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe387c02108190badf9b5051cd9c7a |
completed | May 8, 2026, 7:24 p.m. |
| NEDg | Description generation | batch_69fe3df36364819081a7275b2ac604a6 |
completed | May 8, 2026, 7:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe3e4c9cd08190b83fd437fa96297d |
completed | May 8, 2026, 7:49 p.m. |
Created at: April 9, 2026, 10:09 p.m.