Triple
T9413981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Rosenheim |
E226767
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Rimsting
Rimsting is a small municipality in Bavaria, Germany, situated near Lake Chiemsee and known for its scenic Alpine surroundings.
|
E863060
|
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: Rimsting | Statement: [district of Rosenheim, contains, Rimsting]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rimsting Context triple: [district of Rosenheim, contains, Rimsting]
-
A.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
B.
Ötlingen
Ötlingen is a village-like district of the town of Weil am Rhein in the southwestern German state of Baden-Württemberg, near the borders with France and Switzerland.
-
C.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
D.
Stühlingen
Stühlingen is a small town in the state of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its scenic setting in the Black Forest region.
-
E.
Vellinghausen
Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
- 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: Rimsting Triple: [district of Rosenheim, contains, Rimsting]
Generated description
Rimsting is a small municipality in Bavaria, Germany, situated near Lake Chiemsee and known for its scenic Alpine surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rimsting Target entity description: Rimsting is a small municipality in Bavaria, Germany, situated near Lake Chiemsee and known for its scenic Alpine surroundings.
-
A.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
B.
Ötlingen
Ötlingen is a village-like district of the town of Weil am Rhein in the southwestern German state of Baden-Württemberg, near the borders with France and Switzerland.
-
C.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
D.
Stühlingen
Stühlingen is a small town in the state of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its scenic setting in the Black Forest region.
-
E.
Vellinghausen
Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c680e48190be82e3829e8711f0 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87dfc46e08190bea27c11b987cb6d |
completed | April 10, 2026, 4:35 a.m. |
| NEDg | Description generation | batch_69d8837e70508190b03e8983b2617eac |
completed | April 10, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d889cc40648190a1d80b955e676ea5 |
completed | April 10, 2026, 5:25 a.m. |
Created at: March 30, 2026, 7:47 p.m.