Cancer Prevention Research
E7310
Cancer Prevention Research is a peer-reviewed scientific journal focusing on research aimed at understanding, preventing, and intercepting cancer development.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Cancer Prevention Research canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T77838 — 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: Cancer Prevention Research Context triple: [American Association for Cancer Research, publishes, Cancer Prevention Research]
-
A.
Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention is a peer-reviewed scientific journal focusing on research into the causes, prevention, and early detection of cancer through epidemiologic and biomarker studies.
-
B.
Cancer Research
Cancer Research is a leading peer-reviewed scientific journal that publishes significant findings in oncology, including basic, translational, and clinical cancer research.
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C.
Cancer Discovery
Cancer Discovery is a leading peer-reviewed scientific journal that publishes cutting-edge research and clinical studies in oncology.
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D.
American Association for Cancer Research
The American Association for Cancer Research is a leading professional organization dedicated to advancing cancer research, prevention, diagnosis, and treatment through scientific collaboration and dissemination of findings.
-
E.
National Cancer Institute
The National Cancer Institute is the U.S. federal government’s principal agency for cancer research and training, leading nationwide efforts to prevent, diagnose, and treat cancer.
- 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: Cancer Prevention Research Target entity description: Cancer Prevention Research is a peer-reviewed scientific journal focusing on research aimed at understanding, preventing, and intercepting cancer development.
-
A.
Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention is a peer-reviewed scientific journal focusing on research into the causes, prevention, and early detection of cancer through epidemiologic and biomarker studies.
-
B.
Cancer Research
Cancer Research is a leading peer-reviewed scientific journal that publishes significant findings in oncology, including basic, translational, and clinical cancer research.
-
C.
Cancer Discovery
Cancer Discovery is a leading peer-reviewed scientific journal that publishes cutting-edge research and clinical studies in oncology.
-
D.
American Association for Cancer Research
The American Association for Cancer Research is a leading professional organization dedicated to advancing cancer research, prevention, diagnosis, and treatment through scientific collaboration and dissemination of findings.
-
E.
National Cancer Institute
The National Cancer Institute is the U.S. federal government’s principal agency for cancer research and training, leading nationwide efforts to prevent, diagnose, and treat cancer.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
peer-reviewed journal
ⓘ
scientific journal ⓘ |
| academicDiscipline |
cancer biology
ⓘ
cancer epidemiology ⓘ cancer prevention ⓘ oncology ⓘ |
| coversTopic |
behavioral interventions for cancer prevention
ⓘ
cancer biomarkers ⓘ cancer disparities and prevention ⓘ cancer interception strategies ⓘ cancer risk factors ⓘ cancer screening ⓘ chemoprevention ⓘ clinical trials in cancer prevention ⓘ early detection of cancer ⓘ environmental and occupational carcinogens ⓘ genetic and epigenetic factors in cancer risk ⓘ immunoprevention of cancer ⓘ lifestyle and cancer ⓘ molecular mechanisms of carcinogenesis ⓘ policy and implementation research in cancer prevention ⓘ precision prevention in oncology ⓘ translational cancer prevention research ⓘ |
| focusesOn |
cancer interception
ⓘ
cancer prevention ⓘ understanding cancer development ⓘ |
| goal |
advance knowledge in cancer prevention
ⓘ
improve strategies to prevent cancer ⓘ support translation of prevention research into practice ⓘ |
| hasFormat |
online
ⓘ
print ⓘ |
| hasPeerReviewProcess |
editorial board review
ⓘ
external expert review ⓘ |
| language | English ⓘ |
| peerReviewed | true ⓘ |
| publishes |
commentaries
ⓘ
original research articles ⓘ perspectives ⓘ review articles ⓘ translational research ⓘ |
| subjectArea |
biomedical sciences
ⓘ
preventive medicine ⓘ public health ⓘ |
| targetAudience |
cancer researchers
ⓘ
clinician scientists ⓘ epidemiologists ⓘ oncologists ⓘ public health professionals ⓘ translational researchers ⓘ |
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: Cancer Prevention Research Description of subject: Cancer Prevention Research is a peer-reviewed scientific journal focusing on research aimed at understanding, preventing, and intercepting cancer development.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.