Berkeley Institute for Data Science
E278846
The Berkeley Institute for Data Science is an interdisciplinary research and education center at UC Berkeley that advances data-intensive discovery across the sciences, engineering, and the humanities.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Berkeley Institute for Data Science canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T2573839 — 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: Berkeley Institute for Data Science Context triple: [Department of Statistics (UC Berkeley), collaboratesWith, Berkeley Institute for Data Science]
-
A.
UC Berkeley ASPIRE Lab
UC Berkeley ASPIRE Lab is a research group at the University of California, Berkeley focused on advancing computer architecture and systems, particularly open and energy-efficient computing platforms.
-
B.
MIT Institute for Data, Systems, and Society
The MIT Institute for Data, Systems, and Society is an interdisciplinary research and education institute at the Massachusetts Institute of Technology focused on data science, systems engineering, and social science to address complex societal challenges.
-
C.
Stanford University Department of Statistics
The Stanford University Department of Statistics is a leading academic department renowned for its research and teaching in probability, statistics, and data science.
-
D.
UC Berkeley Parallel Computing Laboratory
The UC Berkeley Parallel Computing Laboratory is a research center at the University of California, Berkeley focused on advancing parallel computer architecture, programming models, and open instruction set technologies such as RISC-V.
-
E.
Department of Electrical Engineering and Computer Sciences, UC Berkeley
The Department of Electrical Engineering and Computer Sciences at UC Berkeley is a leading academic department renowned for its pioneering research and top-ranked programs in electrical engineering, computer science, and related fields.
- 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: Berkeley Institute for Data Science Target entity description: The Berkeley Institute for Data Science is an interdisciplinary research and education center at UC Berkeley that advances data-intensive discovery across the sciences, engineering, and the humanities.
-
A.
UC Berkeley ASPIRE Lab
UC Berkeley ASPIRE Lab is a research group at the University of California, Berkeley focused on advancing computer architecture and systems, particularly open and energy-efficient computing platforms.
-
B.
MIT Institute for Data, Systems, and Society
The MIT Institute for Data, Systems, and Society is an interdisciplinary research and education institute at the Massachusetts Institute of Technology focused on data science, systems engineering, and social science to address complex societal challenges.
-
C.
Stanford University Department of Statistics
The Stanford University Department of Statistics is a leading academic department renowned for its research and teaching in probability, statistics, and data science.
-
D.
UC Berkeley Parallel Computing Laboratory
The UC Berkeley Parallel Computing Laboratory is a research center at the University of California, Berkeley focused on advancing parallel computer architecture, programming models, and open instruction set technologies such as RISC-V.
-
E.
Department of Electrical Engineering and Computer Sciences, UC Berkeley
The Department of Electrical Engineering and Computer Sciences at UC Berkeley is a leading academic department renowned for its pioneering research and top-ranked programs in electrical engineering, computer science, and related fields.
- F. None of above. chosen
Statements (43)
| Predicate | Object |
|---|---|
| instanceOf |
data science institute
ⓘ
education center ⓘ interdisciplinary research center ⓘ research institute ⓘ |
| affiliation | University of California, Berkeley ⓘ |
| campus | UC Berkeley campus ⓘ |
| country |
United States of America
ⓘ
surface form:
United States
|
| fieldOfWork |
artificial intelligence
ⓘ
computational science ⓘ data science ⓘ data-intensive research ⓘ digital humanities ⓘ machine learning ⓘ open science ⓘ reproducible research ⓘ statistics ⓘ |
| focus |
education in data science
ⓘ
interdisciplinary collaboration ⓘ research in data-intensive methods ⓘ tools and infrastructure for data science ⓘ |
| hasPart |
education programs
ⓘ
fellow community ⓘ research programs ⓘ seminar series ⓘ working groups ⓘ |
| languageOfWorkOrName | English ⓘ |
| locatedIn |
Berkeley
ⓘ
surface form:
Berkeley, California
University of California, Berkeley ⓘ |
| mission |
advance data-intensive discovery across disciplines
ⓘ
promote open and reproducible research practices ⓘ support interdisciplinary collaboration in data science ⓘ train the next generation of data scientists ⓘ |
| offers |
fellowship programs
ⓘ
postdoctoral positions ⓘ seminars ⓘ training programs ⓘ workshops ⓘ |
| sector | higher education ⓘ |
| shortName | BIDS ⓘ |
| supports |
collaborative research projects
ⓘ
open-source software projects ⓘ reproducible research practices ⓘ |
| website | https://bids.berkeley.edu/ ⓘ |
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: Berkeley Institute for Data Science Description of subject: The Berkeley Institute for Data Science is an interdisciplinary research and education center at UC Berkeley that advances data-intensive discovery across the sciences, engineering, and the humanities.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.