Beijing Daxing railway station
E429094
Beijing Daxing railway station is a major high-speed rail hub in southern Beijing that connects the city with the emerging Xiong’an New Area and serves the nearby Beijing Daxing International Airport.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Beijing Daxing International Airport (via rail network) | 1 |
| Beijing Daxing International Airport station | 1 |
| Beijing Daxing railway station canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4060667 — 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: Beijing Daxing railway station Context triple: [Beijing–Xiong’an intercity railway, servesStation, Beijing Daxing railway station]
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A.
Beijing South Railway Station
Beijing South Railway Station is a major high-speed rail and transportation hub in Beijing that integrates intercity trains with multiple Beijing Subway lines.
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B.
Beijing West railway station
Beijing West railway station is one of Beijing’s major rail hubs and a key gateway for high-speed and long-distance services connecting the capital with cities across China.
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C.
Beijing Fengtai Railway Station
Beijing Fengtai Railway Station is a major railway hub in Beijing that serves as a key node for high-speed and conventional rail services in the city’s southwestern area.
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D.
Xiong’an railway station
Xiong’an railway station is a major high-speed rail hub in Hebei, China, serving the newly developed Xiong’an New Area and connecting it with Beijing and the wider national rail network.
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E.
Beijing North railway station
Beijing North railway station is a major passenger railway hub in Beijing, serving regional and high-speed routes, including services to the Great Wall area at Badaling.
- 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: Beijing Daxing railway station Target entity description: Beijing Daxing railway station is a major high-speed rail hub in southern Beijing that connects the city with the emerging Xiong’an New Area and serves the nearby Beijing Daxing International Airport.
-
A.
Beijing South Railway Station
Beijing South Railway Station is a major high-speed rail and transportation hub in Beijing that integrates intercity trains with multiple Beijing Subway lines.
-
B.
Beijing West railway station
Beijing West railway station is one of Beijing’s major rail hubs and a key gateway for high-speed and long-distance services connecting the capital with cities across China.
-
C.
Beijing Fengtai Railway Station
Beijing Fengtai Railway Station is a major railway hub in Beijing that serves as a key node for high-speed and conventional rail services in the city’s southwestern area.
-
D.
Xiong’an railway station
Xiong’an railway station is a major high-speed rail hub in Hebei, China, serving the newly developed Xiong’an New Area and connecting it with Beijing and the wider national rail network.
-
E.
Beijing North railway station
Beijing North railway station is a major passenger railway hub in Beijing, serving regional and high-speed routes, including services to the Great Wall area at Badaling.
- F. None of above. chosen
Statements (25)
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: Beijing Daxing railway station Description of subject: Beijing Daxing railway station is a major high-speed rail hub in southern Beijing that connects the city with the emerging Xiong’an New Area and serves the nearby Beijing Daxing International Airport.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Beijing Daxing railway station
linked to: Beijing Daxing railway station