served by Erlangen-Bruck station
E1028758
Served by Erlangen-Bruck station, this area of Erlangen is a district connected to the regional rail network in Bavaria, Germany.
All labels observed (1)
| Label | Occurrences |
|---|---|
| served by Erlangen-Bruck station canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T13214132 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: served by Erlangen-Bruck station Context triple: [Bruck (Erlangen), railwayConnection, served by Erlangen-Bruck station]
-
A.
Aschersleben station
Aschersleben station is a regional railway station in the town of Aschersleben in Saxony-Anhalt, Germany, serving as a local transport hub for passenger rail services.
-
B.
Lichtenfels station
Lichtenfels station is a regional and long-distance railway station in the town of Lichtenfels in Bavaria, Germany, serving as a local transport hub.
-
C.
Nürnberg-Steinbühl station
Nürnberg-Steinbühl station is a local railway station in Nuremberg, Germany, serving regional and S-Bahn commuter services within the city’s rail network.
-
D.
Nürnberg Röthenbach station
Nürnberg Röthenbach station is an underground Nuremberg U-Bahn station in the southwest of the city serving as a key public transport hub for the surrounding residential and commercial areas.
-
E.
Nürnberg-Dürrenhof station
Nürnberg-Dürrenhof station is a local railway stop in Nuremberg, Germany, serving regional and S-Bahn commuter traffic just east of the city’s main station.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: served by Erlangen-Bruck station Target entity description: Served by Erlangen-Bruck station, this area of Erlangen is a district connected to the regional rail network in Bavaria, Germany.
-
A.
Aschersleben station
Aschersleben station is a regional railway station in the town of Aschersleben in Saxony-Anhalt, Germany, serving as a local transport hub for passenger rail services.
-
B.
Lichtenfels station
Lichtenfels station is a regional and long-distance railway station in the town of Lichtenfels in Bavaria, Germany, serving as a local transport hub.
-
C.
Nürnberg-Steinbühl station
Nürnberg-Steinbühl station is a local railway station in Nuremberg, Germany, serving regional and S-Bahn commuter services within the city’s rail network.
-
D.
Nürnberg Röthenbach station
Nürnberg Röthenbach station is an underground Nuremberg U-Bahn station in the southwest of the city serving as a key public transport hub for the surrounding residential and commercial areas.
-
E.
Nürnberg-Dürrenhof station
Nürnberg-Dürrenhof station is a local railway stop in Nuremberg, Germany, serving regional and S-Bahn commuter traffic just east of the city’s main station.
- F. None of above. chosen
Statements (10)
| Predicate | Object |
|---|---|
| instanceOf |
district
ⓘ
urban district ⓘ |
| connectedTo | regional rail network in Bavaria ⓘ |
| country | Germany NERFINISHED ⓘ |
| hasNameInGerman | Erlangen-Bruck NERFINISHED ⓘ |
| hasTransportConnection | railway ⓘ |
| locatedIn |
Bavaria
ⓘ
Middle Franconia NERFINISHED ⓘ |
| partOf | Erlangen NERFINISHED ⓘ |
| servedBy | Erlangen-Bruck station NERFINISHED ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: served by Erlangen-Bruck station Description of subject: Served by Erlangen-Bruck station, this area of Erlangen is a district connected to the regional rail network in Bavaria, Germany.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
Bruck (Erlangen)