Corinna Cortes
E363686
Corinna Cortes is a prominent computer scientist known for her contributions to machine learning and pattern recognition, including co-developing the widely used MNIST dataset and the support vector machine (SVM) framework.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Corinna Cortes canonical | 4 |
How this entity was disambiguated
This entity first appeared as the object of triple T3507176 — 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: Corinna Cortes Context triple: [MNIST, creator, Corinna Cortes]
-
A.
Dario Amodei
Dario Amodei is an AI researcher and entrepreneur, co-founder and CEO of Anthropic and former OpenAI research leader known for his work on large language models and AI safety.
-
B.
Jonathon Shlens
Jonathon Shlens is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work at Google.
-
C.
Pascal Vincent
Pascal Vincent is a Canadian professional ice hockey coach known for serving as head coach of the NHL’s Columbus Blue Jackets and for his extensive coaching career in junior and professional hockey.
-
D.
Samy Bengio
Samy Bengio is a prominent machine learning researcher known for his contributions to deep learning and his leadership roles at major AI organizations including Google and Apple.
-
E.
Ian Goodfellow
Ian Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and co-authoring the influential textbook "Deep Learning."
- 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: Corinna Cortes Target entity description: Corinna Cortes is a prominent computer scientist known for her contributions to machine learning and pattern recognition, including co-developing the widely used MNIST dataset and the support vector machine (SVM) framework.
-
A.
Dario Amodei
Dario Amodei is an AI researcher and entrepreneur, co-founder and CEO of Anthropic and former OpenAI research leader known for his work on large language models and AI safety.
-
B.
Jonathon Shlens
Jonathon Shlens is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work at Google.
-
C.
Pascal Vincent
Pascal Vincent is a Canadian professional ice hockey coach known for serving as head coach of the NHL’s Columbus Blue Jackets and for his extensive coaching career in junior and professional hockey.
-
D.
Samy Bengio
Samy Bengio is a prominent machine learning researcher known for his contributions to deep learning and his leadership roles at major AI organizations including Google and Apple.
-
E.
Ian Goodfellow
Ian Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and co-authoring the influential textbook "Deep Learning."
- F. None of above. chosen
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
person ⓘ researcher ⓘ |
| academicDegree | PhD in computer science ⓘ |
| awardReceived |
ACM Paris Kanellakis Theory and Practice Award
ⓘ
linked to:
Paris Kanellakis Theory and Practice Award
NIPS Test of Time Award ⓘ
linked to:
NeurIPS Test of Time Award
Paris Kanellakis Theory and Practice Award ⓘ |
| citizenship | Danish ⓘ |
| coAuthorOf |
Support-Vector Networks
ⓘ
linked to:
Support Vector Machines
|
| coAuthorWith |
Vladimir Vapnik
ⓘ
Yann LeCun ⓘ |
| coDeveloperOf |
MNIST dataset
ⓘ
linked to:
MNIST
|
| educatedAt |
University of Rochester
ⓘ
Université de Paris-Sud ⓘ
linked to:
Université Paris-Sud
|
| employer |
AT&T Bell Labs
ⓘ
linked to:
Bell Telephone Laboratories
AT&T Labs-Research ⓘ
linked to:
AT&T Labs – Research
Google ⓘ |
| fieldOfWork |
machine learning
ⓘ
pattern recognition ⓘ statistics ⓘ theoretical computer science ⓘ |
| gender | female ⓘ |
| hasResearchInterest |
classification algorithms
ⓘ
data mining ⓘ kernel methods ⓘ large-scale learning ⓘ supervised learning ⓘ |
| influenced |
kernel methods in machine learning
ⓘ
large-margin classification ⓘ supervised learning research ⓘ |
| knownFor |
MNIST dataset
ⓘ
linked to:
MNIST
SVM framework ⓘ machine learning algorithms ⓘ pattern recognition methods ⓘ support vector machines ⓘ |
| languageSpoken |
Danish
ⓘ
English ⓘ French ⓘ |
| memberOf |
Association for Computing Machinery
ⓘ
IEEE ⓘ |
| notableStudent | Mehryar Mohri ⓘ |
| notableWork |
MNIST handwritten digit database
ⓘ
linked to:
MNIST
Support-Vector Networks (1995) ⓘ
linked to:
Support Vector Machines
|
| positionHeld | Head of Google Research New York ⓘ |
| workLocation | New York City ⓘ |
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: Corinna Cortes Description of subject: Corinna Cortes is a prominent computer scientist known for her contributions to machine learning and pattern recognition, including co-developing the widely used MNIST dataset and the support vector machine (SVM) framework.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.