Triple
T22829215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karlsruhe district |
E565749
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Oberhausen-Rheinhausen
Oberhausen-Rheinhausen is a municipality in the German state of Baden-Württemberg, located in the Upper Rhine region.
|
E1557857
|
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: Oberhausen-Rheinhausen | Statement: [Karlsruhe district, contains, Oberhausen-Rheinhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oberhausen-Rheinhausen Context triple: [Karlsruhe district, contains, Oberhausen-Rheinhausen]
-
A.
Oberhausen an der Nahe
Oberhausen an der Nahe is a small winegrowing village in Germany’s Nahe region, known for its high-quality Riesling vineyards along the Nahe River.
-
B.
Oberhausen
Oberhausen is an industrial city in Germany’s Ruhr region, historically known for its coal and steel production and heavily affected by World War II bombing.
-
C.
Oberhausen
Oberhausen is a small Bavarian municipality in southern Germany, situated in the rural district of Weilheim-Schongau.
-
D.
Raunheim
Raunheim is a town in the German state of Hesse, located near Frankfurt am Main and known for its proximity to major transportation routes and Frankfurt Airport.
-
E.
Rüttenscheid
Rüttenscheid is a lively, upscale district of Essen, Germany, known for its bustling shopping streets, restaurants, and cultural venues.
- 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: Oberhausen-Rheinhausen Triple: [Karlsruhe district, contains, Oberhausen-Rheinhausen]
Generated description
Oberhausen-Rheinhausen is a municipality in the German state of Baden-Württemberg, located in the Upper Rhine region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oberhausen-Rheinhausen Target entity description: Oberhausen-Rheinhausen is a municipality in the German state of Baden-Württemberg, located in the Upper Rhine region.
-
A.
Oberhausen an der Nahe
Oberhausen an der Nahe is a small winegrowing village in Germany’s Nahe region, known for its high-quality Riesling vineyards along the Nahe River.
-
B.
Oberhausen
Oberhausen is an industrial city in Germany’s Ruhr region, historically known for its coal and steel production and heavily affected by World War II bombing.
-
C.
Oberhausen
Oberhausen is a small Bavarian municipality in southern Germany, situated in the rural district of Weilheim-Schongau.
-
D.
Raunheim
Raunheim is a town in the German state of Hesse, located near Frankfurt am Main and known for its proximity to major transportation routes and Frankfurt Airport.
-
E.
Rüttenscheid
Rüttenscheid is a lively, upscale district of Essen, Germany, known for its bustling shopping streets, restaurants, and cultural venues.
- 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2a0e308190941064965346f890 |
completed | April 29, 2026, 3:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ba7ac71a881908b7a74a0e2ef99f8 |
completed | May 18, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_6a0baa5bc3f08190b39b53b20884fab8 |
completed | May 19, 2026, 12:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0babb6135481909132713e41bc6939 |
completed | May 19, 2026, 12:15 a.m. |
Created at: April 17, 2026, 3:34 p.m.