Triple
T11279790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhein-Sieg-Kreis |
E267032
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ruppichteroth
Ruppichteroth is a small municipality in western Germany’s North Rhine-Westphalia region, characterized by its rural setting and proximity to the metropolitan area of Cologne-Bonn.
|
E1000315
|
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: Ruppichteroth | Statement: [Rhein-Sieg-Kreis, contains, Ruppichteroth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruppichteroth Context triple: [Rhein-Sieg-Kreis, contains, Ruppichteroth]
-
A.
Geiersthal
Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
-
B.
Kunreuth
Kunreuth is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and historic castle.
-
C.
Geretsried
Geretsried is a town in Upper Bavaria, Germany, situated on the Isar River and known as the largest town in the Bad Tölz-Wolfratshausen district.
-
D.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
E.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
- 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: Ruppichteroth Triple: [Rhein-Sieg-Kreis, contains, Ruppichteroth]
Generated description
Ruppichteroth is a small municipality in western Germany’s North Rhine-Westphalia region, characterized by its rural setting and proximity to the metropolitan area of Cologne-Bonn.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ruppichteroth Target entity description: Ruppichteroth is a small municipality in western Germany’s North Rhine-Westphalia region, characterized by its rural setting and proximity to the metropolitan area of Cologne-Bonn.
-
A.
Geiersthal
Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
-
B.
Kunreuth
Kunreuth is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and historic castle.
-
C.
Geretsried
Geretsried is a town in Upper Bavaria, Germany, situated on the Isar River and known as the largest town in the Bad Tölz-Wolfratshausen district.
-
D.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
E.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e969b3448190940e2bd499d2d7de |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c5a9dc881909b695f7e87dfcdf6 |
completed | May 2, 2026, 10:36 p.m. |
| NEDg | Description generation | batch_69f67db4dd2081909a238e368645e899 |
completed | May 2, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67ececce8819080335e67bd747057 |
completed | May 2, 2026, 10:46 p.m. |
Created at: April 8, 2026, 9:31 p.m.