Peking Union Medical College Hospital, Beijing, Republic of China
E179677
Peking Union Medical College Hospital in Beijing is a leading Chinese teaching and research hospital historically associated with major political and medical events in modern China.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Peking Union Medical College Hospital, Beijing, Republic of China canonical | 2 |
| PUMCH | 1 |
| Peking Union Medical College Hospital | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1569079 — 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: Peking Union Medical College Hospital, Beijing, Republic of China Context triple: [Sun Yat-sen, deathPlace, Peking Union Medical College Hospital, Beijing, Republic of China]
-
A.
China Medical University (Shenyang)
China Medical University (Shenyang) is a major Chinese medical university known for its comprehensive medical education, research, and affiliated hospitals, located in Shenyang, Liaoning Province.
-
B.
Tianjin Medical University
Tianjin Medical University is a major Chinese medical institution known for its education and research in clinical medicine, public health, and biomedical sciences.
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C.
Institute of Medical Science, University of Tokyo
The Institute of Medical Science, University of Tokyo is a leading Japanese biomedical research and graduate education center renowned for its work in infectious diseases, genomics, and advanced medical science.
-
D.
Peking University
Peking University is a leading Chinese research university in Beijing, renowned for its academic excellence, historical significance, and global influence.
-
E.
University of Tokyo Hospital
University of Tokyo Hospital is a major academic medical center in Tokyo, Japan, known for advanced clinical care, medical education, and cutting-edge research.
- 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: Peking Union Medical College Hospital, Beijing, Republic of China Target entity description: Peking Union Medical College Hospital in Beijing is a leading Chinese teaching and research hospital historically associated with major political and medical events in modern China.
-
A.
China Medical University (Shenyang)
China Medical University (Shenyang) is a major Chinese medical university known for its comprehensive medical education, research, and affiliated hospitals, located in Shenyang, Liaoning Province.
-
B.
Tianjin Medical University
Tianjin Medical University is a major Chinese medical institution known for its education and research in clinical medicine, public health, and biomedical sciences.
-
C.
Institute of Medical Science, University of Tokyo
The Institute of Medical Science, University of Tokyo is a leading Japanese biomedical research and graduate education center renowned for its work in infectious diseases, genomics, and advanced medical science.
-
D.
Peking University
Peking University is a leading Chinese research university in Beijing, renowned for its academic excellence, historical significance, and global influence.
-
E.
University of Tokyo Hospital
University of Tokyo Hospital is a major academic medical center in Tokyo, Japan, known for advanced clinical care, medical education, and cutting-edge research.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
general hospital
ⓘ
research hospital ⓘ teaching hospital ⓘ |
| affiliatedWith |
Chinese Academy of Medical Sciences
ⓘ
Peking Union Medical College ⓘ |
| alsoKnownAs |
Beijing Xiehe Yiyuan
ⓘ
Peking Union Medical College Hospital, Beijing, Republic of China ⓘ
surface form:
PUMCH
Xiehe Hospital ⓘ |
| country | China ⓘ |
| foundedBy | Rockefeller Foundation ⓘ |
| governedBy | National Health Commission of the People’s Republic of China ⓘ |
| hasAcademicRole |
clinical teaching hospital
ⓘ
teaching base for Peking Union Medical College ⓘ |
| hasEmergencyService | yes ⓘ |
| hasFunction |
clinical care
ⓘ
medical education ⓘ medical research ⓘ |
| hasInpatientServices | yes ⓘ |
| hasIntensiveCareUnit | yes ⓘ |
| hasNotableStatus |
influential in Chinese medical policy and practice
ⓘ
key national hospital in China ⓘ |
| hasOutpatientServices | yes ⓘ |
| hasReputation |
leading research hospital in China
ⓘ
national referral center ⓘ top-tier hospital in China ⓘ |
| historicallyAssociatedWith |
major medical events in modern China
ⓘ
major political events in modern China ⓘ modern medical development in China ⓘ |
| languageOfName | Chinese ⓘ |
| locatedIn | Beijing ⓘ |
| locatedInAdministrativeTerritory | Dongcheng District, Beijing ⓘ |
| offersTrainingProgram |
fellowship training
ⓘ
medical student clinical rotations ⓘ residency training ⓘ |
| operatedBy | Chinese Academy of Medical Sciences ⓘ |
| participatesIn |
clinical trials
ⓘ
national medical research programs ⓘ |
| specializesIn |
cardiology
ⓘ
endocrinology ⓘ infectious diseases ⓘ internal medicine ⓘ nephrology ⓘ neurology ⓘ obstetrics and gynecology ⓘ oncology ⓘ pediatrics ⓘ surgery ⓘ |
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: Peking Union Medical College Hospital, Beijing, Republic of China Description of subject: Peking Union Medical College Hospital in Beijing is a leading Chinese teaching and research hospital historically associated with major political and medical events in modern China.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Peking Union Medical College Hospital
Peking Union Medical College Hospital, Beijing, Republic of China
→
alsoKnownAs
→
Peking Union Medical College Hospital, Beijing, Republic of China
ⓘ
subject surface form:
Peking Union Medical College Hospital
this entity surface form:
PUMCH