Jeff Heer
E395926
Jeff Heer is an American computer scientist and professor best known for his influential work in data visualization and for co-creating tools like D3.js and the Vega visualization grammar.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Jeff Heer canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3865792 — 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: Jeff Heer Context triple: [Pat Hanrahan, notableStudent, Jeff Heer]
-
A.
Jeffrey Auerbach
Jeffrey Auerbach is a film producer best known for his work on the stop-motion animated feature "Corpse Bride."
-
B.
Christopher Lennertz
Christopher Lennertz is an American composer best known for his film, television, and video game scores, including work on major comedies, action films, and popular series like Supernatural.
-
C.
Gary K. Wolf
Gary K. Wolf is an American author best known for creating the character Roger Rabbit and writing the novel that inspired the film "Who Framed Roger Rabbit."
-
D.
Ben Templesmith
Ben Templesmith is an Australian comic book artist and writer best known for his distinctive, atmospheric horror artwork on titles such as "30 Days of Night" and "Fell."
-
E.
Barton Myers
Barton Myers is a Canadian-American architect renowned for his innovative urban infill projects and prominent cultural and civic buildings across North America.
- 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: Jeff Heer Target entity description: Jeff Heer is an American computer scientist and professor best known for his influential work in data visualization and for co-creating tools like D3.js and the Vega visualization grammar.
-
A.
Jeffrey Auerbach
Jeffrey Auerbach is a film producer best known for his work on the stop-motion animated feature "Corpse Bride."
-
B.
Christopher Lennertz
Christopher Lennertz is an American composer best known for his film, television, and video game scores, including work on major comedies, action films, and popular series like Supernatural.
-
C.
Gary K. Wolf
Gary K. Wolf is an American author best known for creating the character Roger Rabbit and writing the novel that inspired the film "Who Framed Roger Rabbit."
-
D.
Ben Templesmith
Ben Templesmith is an Australian comic book artist and writer best known for his distinctive, atmospheric horror artwork on titles such as "30 Days of Night" and "Fell."
-
E.
Barton Myers
Barton Myers is a Canadian-American architect renowned for his innovative urban infill projects and prominent cultural and civic buildings across North America.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
data visualization researcher ⓘ human ⓘ university professor ⓘ |
| awardReceived |
ACM CHI Best Paper Award
ⓘ
linked to:
ACM SIGCHI awards program
ACM Grace Murray Hopper Award ⓘ
linked to:
Grace Murray Hopper Award
IEEE Visualization Technical Achievement Award ⓘ |
| basedIn |
Seattle, Washington
ⓘ
linked to:
Seattle, Washington, United States
|
| coCreatorOf |
D3.js
ⓘ
Protovis ⓘ Vega ⓘ Vega-Lite ⓘ |
| countryOfCitizenship | United States of America ⓘ |
| doctoralAdvisor | Maneesh Agrawala ⓘ |
| educatedAt |
University of California, Berkeley
ⓘ
University of California, San Diego ⓘ |
| employer | University of Washington ⓘ |
| fieldOfStudy | computer science ⓘ |
| fieldOfWork |
data science
ⓘ
data visualization ⓘ human-computer interaction ⓘ information visualization ⓘ visual analytics ⓘ |
| hasCreated | Interactive Data Lab at the University of Washington ⓘ |
| hasRole |
software developer in visualization
ⓘ
tool designer ⓘ |
| knownFor |
D3.js
ⓘ
Protovis ⓘ Vega visualization grammar ⓘ Vega-Lite ⓘ interactive data visualization ⓘ |
| languageSpoken | English ⓘ |
| memberOf |
Association for Computing Machinery
ⓘ
IEEE Computer Society ⓘ |
| notableWork |
“A Tour through the Visualization Zoo”
ⓘ
“D3: Data-Driven Documents” ⓘ “Vega: A Declarative Visualization Grammar” ⓘ
linked to:
Vega visualization grammar
|
| occupation |
computer scientist
ⓘ
professor ⓘ |
| positionHeld |
Director of the Interactive Data Lab at the University of Washington
ⓘ
Professor of Computer Science & Engineering at the University of Washington ⓘ |
| researchInterest |
data-driven documents
ⓘ
interactive visualization ⓘ perception in visualization ⓘ user-centered design ⓘ visualization grammars ⓘ |
| workInstitution | University of Washington Paul G. Allen School of Computer Science & Engineering ⓘ |
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: Jeff Heer Description of subject: Jeff Heer is an American computer scientist and professor best known for his influential work in data visualization and for co-creating tools like D3.js and the Vega visualization grammar.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.