Jong Wook Kim
E445531
Jong Wook Kim is a machine learning researcher known for his contributions to multimodal models, including work on the development of CLIP at OpenAI.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Jong Wook Kim canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4424866 — 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: Jong Wook Kim Context triple: [CLIP, introducedBy, Jong Wook Kim]
-
A.
Yong-taek Jung
Yong-taek Jung is a notable individual recognized for bearing the Korean surname Jung.
-
B.
Yong-gi Jung
Yong-gi Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
C.
Sung-kyu Jung
Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
D.
Ho-seok Jung
Ho-seok Jung is a notable individual recognized for achievements significant enough to be associated with the surname Jung.
-
E.
Yong-jun Jung
Yong-jun Jung is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Jung.
- 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: Jong Wook Kim Target entity description: Jong Wook Kim is a machine learning researcher known for his contributions to multimodal models, including work on the development of CLIP at OpenAI.
-
A.
Yong-taek Jung
Yong-taek Jung is a notable individual recognized for bearing the Korean surname Jung.
-
B.
Yong-gi Jung
Yong-gi Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
C.
Sung-kyu Jung
Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
D.
Ho-seok Jung
Ho-seok Jung is a notable individual recognized for achievements significant enough to be associated with the surname Jung.
-
E.
Yong-jun Jung
Yong-jun Jung is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Jung.
- F. None of above. chosen
Statements (23)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
machine learning researcher ⓘ |
| affiliation | OpenAI NERFINISHED ⓘ |
| contributedTo | CLIP: Connecting Text and Images NERFINISHED ⓘ |
| countryOfWork |
United States of America
ⓘ
surface form:
United States
|
| fieldOfWork |
artificial intelligence
ⓘ
computer vision ⓘ machine learning ⓘ multimodal learning ⓘ natural language processing ⓘ |
| hasRole | research scientist ⓘ |
| knownFor |
CLIP
NERFINISHED
ⓘ
contrastive learning ⓘ multimodal machine learning ⓘ representation learning ⓘ |
| languageOfWork | English ⓘ |
| notableFor | developing multimodal models at OpenAI ⓘ |
| notableWork | CLIP NERFINISHED ⓘ |
| researchInterest |
large-scale pretraining
ⓘ
multimodal representation learning ⓘ self-supervised learning ⓘ vision-language models ⓘ |
| worksAt | OpenAI NERFINISHED ⓘ |
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: Jong Wook Kim Description of subject: Jong Wook Kim is a machine learning researcher known for his contributions to multimodal models, including work on the development of CLIP at OpenAI.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.