Tom B. Brown
E471343
Tom B. Brown is a machine learning researcher known for leading work on large-scale language models, including the influential GPT-3 paper "Language Models are Few-Shot Learners."
All labels observed (1)
| Label | Occurrences |
|---|---|
| Tom B. Brown canonical | 12 |
How this entity was disambiguated
This entity first appeared as the object of triple T4651186 — 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: Tom B. Brown Context triple: [Language Models are Few-Shot Learners, author, Tom B. Brown]
-
A.
Thomas J. Brown
Thomas J. Brown is an American Episcopal bishop who serves as the diocesan leader of the Episcopal Diocese of Maine.
-
B.
J. Douglas Brown
J. Douglas Brown was an American economist and academic who played a key role in shaping U.S. Social Security policy during the New Deal era.
-
C.
John Ketcham
John Ketcham is a film producer best known for his work on the biographical sports drama "The Hurricane."
-
D.
Ralph Miller
Ralph Miller was a highly respected American college basketball coach best known for transforming Oregon State University into a national contender during his long tenure.
-
E.
David Broyles
David Broyles is one of the children of American screenwriter and Vietnam War veteran William Broyles Jr.
- 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: Tom B. Brown Target entity description: Tom B. Brown is a machine learning researcher known for leading work on large-scale language models, including the influential GPT-3 paper "Language Models are Few-Shot Learners."
-
A.
Thomas J. Brown
Thomas J. Brown is an American Episcopal bishop who serves as the diocesan leader of the Episcopal Diocese of Maine.
-
B.
J. Douglas Brown
J. Douglas Brown was an American economist and academic who played a key role in shaping U.S. Social Security policy during the New Deal era.
-
C.
John Ketcham
John Ketcham is a film producer best known for his work on the biographical sports drama "The Hurricane."
-
D.
Ralph Miller
Ralph Miller was a highly respected American college basketball coach best known for transforming Oregon State University into a national contender during his long tenure.
-
E.
David Broyles
David Broyles is one of the children of American screenwriter and Vietnam War veteran William Broyles Jr.
- F. None of above. chosen
Statements (58)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
machine learning researcher ⓘ |
| affiliation | OpenAI ⓘ |
| coAuthorOf |
"Language Models are Few-Shot Learners"
ⓘ
linked to:
Language Models are Few-Shot Learners
|
| coAuthorWith |
Aditya Ramesh
ⓘ
Alec Radford ⓘ Amanda Askell ⓘ Ariel Herbert-Voss ⓘ Arvind Neelakantan ⓘ Benjamin Chess ⓘ Benjamin Mann ⓘ Christopher Berner ⓘ Christopher Hesse ⓘ Clemens Winter ⓘ Daniel M. Ziegler ⓘ Dario Amodei ⓘ Eric Sigler ⓘ Girish Sastry ⓘ Gretchen Krueger ⓘ Ilya Sutskever ⓘ Jack Clark ⓘ Jared Kaplan ⓘ Jeffrey Wu ⓘ Mark Chen ⓘ Mateusz Litwin ⓘ Melanie Subbiah ⓘ Nick Ryder ⓘ Prafulla Dhariwal ⓘ Pranav Shyam ⓘ Rewon Child ⓘ Sam McCandlish ⓘ Sandhini Agarwal ⓘ Scott Gray ⓘ Tom Henighan ⓘ |
| contributedTo | development of GPT-3 API ⓘ |
| countryOfCitizenship |
United States
ⓘ
linked to:
United States of America
|
| employer | OpenAI ⓘ |
| fieldOfWork |
artificial intelligence
ⓘ
deep learning ⓘ large language models ⓘ natural language processing ⓘ |
| hasGivenTalkOn |
few-shot learning with GPT-3
ⓘ
large language models ⓘ |
| influenced |
adoption of large language models in industry
ⓘ
research on few-shot learning with language models ⓘ |
| knownFor |
GPT-3
ⓘ
large-scale language models ⓘ paper "Language Models are Few-Shot Learners" ⓘ
linked to:
Language Models are Few-Shot Learners
|
| language | English ⓘ |
| notableWork |
"Language Models are Few-Shot Learners"
ⓘ
linked to:
Language Models are Few-Shot Learners
|
| paperPresentedAt |
NeurIPS 2020
ⓘ
linked to:
NeurIPS
|
| publicationVenue |
NeurIPS 2020
ⓘ
linked to:
NeurIPS
|
| researchInterest |
few-shot learning
ⓘ
scaling laws for language models ⓘ transformer architectures ⓘ unsupervised learning ⓘ |
| role | research scientist at OpenAI ⓘ |
| workOn | GPT-3 ⓘ |
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: Tom B. Brown Description of subject: Tom B. Brown is a machine learning researcher known for leading work on large-scale language models, including the influential GPT-3 paper "Language Models are Few-Shot Learners."
Referenced by (12)
Full triples — surface form annotated when it differs from this entity's canonical label.