Raghu Ramakrishnan
E360726
Raghu Ramakrishnan is a prominent computer scientist known for his influential work in database systems and data mining, including contributions to query optimization and scalable data analysis.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Raghu Ramakrishnan canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T3425619 — 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: Raghu Ramakrishnan Context triple: [SIGKDD Innovation Award, notableRecipient, Raghu Ramakrishnan]
-
A.
Rakesh Agrawal
Rakesh Agrawal is a pioneering computer scientist best known for his foundational contributions to data mining and database systems.
-
B.
Charu C. Aggarwal
Charu C. Aggarwal is a prominent computer scientist and researcher known for his influential contributions to data mining, machine learning, and high-dimensional data analysis.
-
C.
Jeffrey D. Ullman
Jeffrey D. Ullman is a prominent American computer scientist known for his foundational contributions to database theory, algorithms, and formal languages, and for coauthoring several classic textbooks in computer science.
-
D.
Laxman Narasimhan
Laxman Narasimhan is an Indian-American business executive best known as the chief executive officer of Starbucks and former CEO of Reckitt Benckiser.
-
E.
Jim Gray
Jim Gray was a pioneering computer scientist renowned for his foundational work in database systems and transaction processing, which earned him numerous top honors in the field.
- 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: Raghu Ramakrishnan Target entity description: Raghu Ramakrishnan is a prominent computer scientist known for his influential work in database systems and data mining, including contributions to query optimization and scalable data analysis.
-
A.
Rakesh Agrawal
Rakesh Agrawal is a pioneering computer scientist best known for his foundational contributions to data mining and database systems.
-
B.
Charu C. Aggarwal
Charu C. Aggarwal is a prominent computer scientist and researcher known for his influential contributions to data mining, machine learning, and high-dimensional data analysis.
-
C.
Jeffrey D. Ullman
Jeffrey D. Ullman is a prominent American computer scientist known for his foundational contributions to database theory, algorithms, and formal languages, and for coauthoring several classic textbooks in computer science.
-
D.
Laxman Narasimhan
Laxman Narasimhan is an Indian-American business executive best known as the chief executive officer of Starbucks and former CEO of Reckitt Benckiser.
-
E.
Jim Gray
Jim Gray was a pioneering computer scientist renowned for his foundational work in database systems and transaction processing, which earned him numerous top honors in the field.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
author
ⓘ
computer scientist ⓘ researcher ⓘ |
| academicDegree |
Bachelor of Technology in Electrical Engineering
ⓘ
PhD in Computer Science ⓘ |
| coAuthor |
Hector Garcia-Molina
ⓘ
Jiawei Han ⓘ Johannes Gehrke ⓘ |
| doctoralAdvisor | Don Fussell ⓘ |
| educatedAt |
Indian Institute of Technology Madras
ⓘ
University of Texas at Austin ⓘ |
| employer |
Microsoft
ⓘ
University of Wisconsin–Madison ⓘ Yahoo! ⓘ
linked to:
Yahoo
|
| fieldOfWork |
data mining
ⓘ
database systems ⓘ query optimization ⓘ scalable data analysis ⓘ |
| hasAward |
ACM SIGMOD Contributions Award
ⓘ
ACM SIGMOD Test of Time Award ⓘ VLDB 10-Year Best Paper Award ⓘ
linked to:
VLDB Test of Time Award
|
| hasCitizenship |
India
ⓘ
United States of America ⓘ |
| influencedBy | relational database theory ⓘ |
| knownFor |
contributions to query optimization
ⓘ
contributions to scalable data analysis ⓘ work on data mining ⓘ work on data warehousing ⓘ work on database systems ⓘ work on deductive databases ⓘ work on large-scale data platforms ⓘ work on recommender systems ⓘ |
| languageSpoken |
English
ⓘ
Hindi ⓘ Tamil ⓘ |
| memberOf |
ACM SIGMOD community
ⓘ
linked to:
SIGMOD
Association for Computing Machinery ⓘ |
| notableWork |
Data Mining: Concepts and Techniques
ⓘ
Database Management Systems ⓘ |
| positionHeld |
Chief Scientist for Audience and Cloud Computing at Yahoo!
ⓘ
Professor of Computer Sciences at University of Wisconsin–Madison ⓘ Technical Fellow at Microsoft ⓘ
linked to:
Microsoft Technical Fellow
Vice President at Microsoft ⓘ |
| researchInterest |
cloud data platforms
ⓘ
data warehousing ⓘ deductive databases ⓘ probabilistic databases ⓘ web-scale data management ⓘ |
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: Raghu Ramakrishnan Description of subject: Raghu Ramakrishnan is a prominent computer scientist known for his influential work in database systems and data mining, including contributions to query optimization and scalable data analysis.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.