Xiehe Hospital
E676264
Xiehe Hospital is a leading tertiary teaching hospital in Beijing renowned for its high-quality medical care, research, and affiliation with Peking Union Medical College.
All labels observed (5)
| Label | Occurrences |
|---|---|
| Peking Union Medical College Hospital | 3 |
| Xiehe Hospital canonical | 2 |
| Beijing Xiehe Hospital | 1 |
| PUMCH | 1 |
| 北京协和医院 | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7588570 — 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: Xiehe Hospital Context triple: [Peking Union Medical College Hospital, alsoKnownAs, Xiehe Hospital]
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A.
Sun Yat-sen Memorial Hospital
Sun Yat-sen Memorial Hospital is a major teaching and research hospital in China affiliated with Sun Yat-sen University.
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B.
Dubbo Base Hospital
Dubbo Base Hospital is a major public healthcare facility in Dubbo, New South Wales, providing a wide range of medical and emergency services to the city and surrounding regional communities.
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C.
Shanghai Jiao Tong University Affiliated Ruijin Hospital
Shanghai Jiao Tong University Affiliated Ruijin Hospital is a major teaching and research hospital in Shanghai renowned for its comprehensive clinical services and medical education.
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D.
Shanghai Jiao Tong University Affiliated Renji Hospital
Shanghai Jiao Tong University Affiliated Renji Hospital is a major teaching and research hospital in Shanghai known for its comprehensive medical services and academic excellence.
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E.
Wuhan Union Hospital
Wuhan Union Hospital is a major comprehensive teaching and research hospital in Wuhan, China, affiliated with Tongji Medical College of Huazhong University of Science and Technology.
- 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: Xiehe Hospital Target entity description: Xiehe Hospital is a leading tertiary teaching hospital in Beijing renowned for its high-quality medical care, research, and affiliation with Peking Union Medical College.
-
A.
Sun Yat-sen Memorial Hospital
Sun Yat-sen Memorial Hospital is a major teaching and research hospital in China affiliated with Sun Yat-sen University.
-
B.
Dubbo Base Hospital
Dubbo Base Hospital is a major public healthcare facility in Dubbo, New South Wales, providing a wide range of medical and emergency services to the city and surrounding regional communities.
-
C.
Shanghai Jiao Tong University Affiliated Ruijin Hospital
Shanghai Jiao Tong University Affiliated Ruijin Hospital is a major teaching and research hospital in Shanghai renowned for its comprehensive clinical services and medical education.
-
D.
Shanghai Jiao Tong University Affiliated Renji Hospital
Shanghai Jiao Tong University Affiliated Renji Hospital is a major teaching and research hospital in Shanghai known for its comprehensive medical services and academic excellence.
-
E.
Wuhan Union Hospital
Wuhan Union Hospital is a major comprehensive teaching and research hospital in Wuhan, China, affiliated with Tongji Medical College of Huazhong University of Science and Technology.
- F. None of above. chosen
Statements (52)
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: Xiehe Hospital Description of subject: Xiehe Hospital is a leading tertiary teaching hospital in Beijing renowned for its high-quality medical care, research, and affiliation with Peking Union Medical College.
Referenced by (8)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject linked to:
Peking Union Medical College Hospital, Beijing, Republic of China
linked to: Xiehe Hospital
linked to: Xiehe Hospital
linked to: Xiehe Hospital
linked to: Xiehe Hospital
linked to: Xiehe Hospital
linked to: Xiehe Hospital