Trevor Darrell
E1017402
Trevor Darrell is a prominent computer vision and machine learning researcher and professor known for his work on deep learning, visual recognition, and autonomous systems.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Trevor Darrell canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T13061788 — 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: Trevor Darrell Context triple: [Jitendra Malik, notableStudent, Trevor Darrell]
-
A.
Trevor Albert
Trevor Albert is a film producer best known for his work on the classic comedy "Groundhog Day."
-
B.
Trevor Blackwell
Trevor Blackwell is a Canadian engineer, entrepreneur, and roboticist best known as a co-founder of the startup accelerator Y Combinator and for his work in humanoid and self-balancing robots.
-
C.
Trevor Duncan
Trevor Duncan was a British composer best known for his prolific production music and film scores in the mid-20th century.
-
D.
Trevor Jim
Trevor Jim was a computer scientist and cryptographer known for his work on programming languages, security, and formal methods.
-
E.
Trevor Hawkins
Trevor Hawkins is a relatively obscure individual whose specific public achievements or profession are not widely documented.
- 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: Trevor Darrell Target entity description: Trevor Darrell is a prominent computer vision and machine learning researcher and professor known for his work on deep learning, visual recognition, and autonomous systems.
-
A.
Trevor Albert
Trevor Albert is a film producer best known for his work on the classic comedy "Groundhog Day."
-
B.
Trevor Blackwell
Trevor Blackwell is a Canadian engineer, entrepreneur, and roboticist best known as a co-founder of the startup accelerator Y Combinator and for his work in humanoid and self-balancing robots.
-
C.
Trevor Duncan
Trevor Duncan was a British composer best known for his prolific production music and film scores in the mid-20th century.
-
D.
Trevor Jim
Trevor Jim was a computer scientist and cryptographer known for his work on programming languages, security, and formal methods.
-
E.
Trevor Hawkins
Trevor Hawkins is a relatively obscure individual whose specific public achievements or profession are not widely documented.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
computer vision researcher
ⓘ
machine learning researcher ⓘ person ⓘ university professor ⓘ |
| citizenship |
United States of America
ⓘ
surface form:
United States
|
| fieldOfWork |
artificial intelligence
ⓘ
autonomous systems ⓘ computer vision ⓘ deep learning ⓘ machine learning ⓘ visual recognition ⓘ |
| gender | male ⓘ |
| hasAcademicPosition |
faculty member
ⓘ
professor ⓘ |
| influencedField |
autonomous driving research
ⓘ
deep learning for perception ⓘ modern computer vision ⓘ |
| knownFor |
autonomous driving perception systems
ⓘ
context-based visual recognition ⓘ deep learning for visual recognition ⓘ domain adaptation in computer vision ⓘ large-scale visual recognition datasets and benchmarks ⓘ multimodal learning for vision and language ⓘ object recognition in images and video ⓘ |
| notableContribution |
advances in domain adaptation for visual recognition
ⓘ
development of deep learning methods for image recognition ⓘ methods for context-aware object detection ⓘ research on perception for autonomous driving systems ⓘ work on integrating vision with natural language ⓘ |
| occupation |
computer scientist
ⓘ
professor ⓘ researcher ⓘ |
| researchInterest |
autonomous vehicles
ⓘ
deep neural networks ⓘ human-robot interaction ⓘ object detection ⓘ representation learning ⓘ robust perception in real-world environments ⓘ scene understanding ⓘ segmentation ⓘ transfer learning in vision ⓘ vision-language models ⓘ |
| worksOn |
autonomous systems perception
ⓘ
deep learning architectures for vision ⓘ interactive and embodied AI systems ⓘ large-scale visual recognition systems ⓘ learning from weakly labeled visual data ⓘ |
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: Trevor Darrell Description of subject: Trevor Darrell is a prominent computer vision and machine learning researcher and professor known for his work on deep learning, visual recognition, and autonomous systems.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.