Tsinghua University-affiliated hospitals
E930417
Tsinghua University-affiliated hospitals are a network of teaching and research medical centers in China that provide clinical training and healthcare services in partnership with Tsinghua University’s School of Medicine.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Tsinghua University-affiliated hospitals canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T11507696 — 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: Tsinghua University-affiliated hospitals Context triple: [School of Medicine, Tsinghua University, affiliatedWith, Tsinghua University-affiliated hospitals]
-
A.
Peking University Medical School
Peking University Medical School is a leading Chinese medical education and research institution renowned for training prominent physicians and scientists, including Nobel laureate Tu Youyou.
-
B.
Huashan Hospital affiliated to Fudan University
Huashan Hospital affiliated to Fudan University is a major teaching and research hospital in Shanghai renowned for its advanced medical services and clinical specialties.
-
C.
Zhongshan Hospital affiliated to Fudan University
Zhongshan Hospital affiliated to Fudan University is a major teaching and research hospital in Shanghai renowned for its comprehensive medical services and clinical excellence.
-
D.
Chinese Academy of Medical Sciences
The Chinese Academy of Medical Sciences is a leading national medical research institution in China, renowned for its comprehensive biomedical research, education, and clinical innovation.
-
E.
Peking Union Medical College Hospital, Beijing, Republic of China
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.
- 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: Tsinghua University-affiliated hospitals Target entity description: Tsinghua University-affiliated hospitals are a network of teaching and research medical centers in China that provide clinical training and healthcare services in partnership with Tsinghua University’s School of Medicine.
-
A.
Peking University Medical School
Peking University Medical School is a leading Chinese medical education and research institution renowned for training prominent physicians and scientists, including Nobel laureate Tu Youyou.
-
B.
Huashan Hospital affiliated to Fudan University
Huashan Hospital affiliated to Fudan University is a major teaching and research hospital in Shanghai renowned for its advanced medical services and clinical specialties.
-
C.
Zhongshan Hospital affiliated to Fudan University
Zhongshan Hospital affiliated to Fudan University is a major teaching and research hospital in Shanghai renowned for its comprehensive medical services and clinical excellence.
-
D.
Chinese Academy of Medical Sciences
The Chinese Academy of Medical Sciences is a leading national medical research institution in China, renowned for its comprehensive biomedical research, education, and clinical innovation.
-
E.
Peking Union Medical College Hospital, Beijing, Republic of China
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.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
medical education network
ⓘ
network of teaching hospitals ⓘ |
| affiliatedWith |
Tsinghua University
NERFINISHED
ⓘ
Tsinghua University School of Medicine NERFINISHED ⓘ |
| collaboratesWith |
Beijing municipal health authorities
NERFINISHED
ⓘ
other university-affiliated hospitals in China ⓘ |
| country | China ⓘ |
| educates |
allied health professionals
ⓘ
nurses ⓘ physicians ⓘ |
| field |
clinical medicine
ⓘ
medical education ⓘ medicine ⓘ |
| focusesOn |
integration of teaching and clinical practice
ⓘ
interdisciplinary collaboration with engineering ⓘ interdisciplinary collaboration with life sciences ⓘ translational medical research ⓘ |
| goal |
advance clinical research outcomes
ⓘ
improve quality of medical education ⓘ provide high-level medical services ⓘ |
| hasCharacteristic |
research-intensive
ⓘ
teaching-oriented ⓘ tertiary care level ⓘ |
| hasFunction |
clinical training
ⓘ
healthcare services ⓘ medical research ⓘ |
| hasPart |
Beijing Tsinghua Changgung Hospital
NERFINISHED
ⓘ
Tsinghua University First Hospital NERFINISHED ⓘ Tsinghua University Second Hospital NERFINISHED ⓘ Tsinghua University Yuquan Hospital NERFINISHED ⓘ specialized clinical centers ⓘ |
| languageOfWorkOrName | Chinese ⓘ |
| locatedIn | Beijing ⓘ |
| offers |
continuing medical education
ⓘ
postgraduate residency training ⓘ specialty fellowship training ⓘ undergraduate clinical rotations ⓘ |
| operatedBy | Tsinghua University NERFINISHED ⓘ |
| partOf | Tsinghua University medical system NERFINISHED ⓘ |
| regulates | clinical training standards for affiliated units ⓘ |
| serves |
Tsinghua University graduate students in medicine
ⓘ
Tsinghua University medical students ⓘ local community patients ⓘ referral patients from other regions ⓘ |
| uses |
evidence-based medicine guidelines
ⓘ
modern medical technology ⓘ |
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: Tsinghua University-affiliated hospitals Description of subject: Tsinghua University-affiliated hospitals are a network of teaching and research medical centers in China that provide clinical training and healthcare services in partnership with Tsinghua University’s School of Medicine.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
School of Medicine, Tsinghua University