Noel Kate Cho
E737526
Noel Kate Cho is a young actress best known for her role in the acclaimed film "Minari."
All labels observed (1)
| Label | Occurrences |
|---|---|
| Noel Kate Cho canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8450902 — 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: Noel Kate Cho Context triple: [Minari, stars, Noel Kate Cho]
-
A.
Cheryl Song
Cheryl Song is an American dancer and actress best known as a featured Soul Train dancer who also appeared in the 1988 action film "Action Jackson."
-
B.
Willa Kim
Willa Kim was an acclaimed American costume designer known for her vibrant, innovative work on Broadway, ballet, and opera, earning multiple Tony Awards over her career.
-
C.
Julia Cho
Julia Cho is an American playwright and screenwriter known for her work on stage and in film, including co-writing Pixar’s animated feature "Turning Red."
-
D.
Julie Oh
Julie Oh is a film producer known for her work on projects such as the musical drama "Tick, Tick... Boom!" (2021).
-
E.
Christina Oh
Christina Oh is an American film producer best known for her work on acclaimed independent films, including the Oscar-nominated drama "Minari."
- 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: Noel Kate Cho Target entity description: Noel Kate Cho is a young actress best known for her role in the acclaimed film "Minari."
-
A.
Cheryl Song
Cheryl Song is an American dancer and actress best known as a featured Soul Train dancer who also appeared in the 1988 action film "Action Jackson."
-
B.
Willa Kim
Willa Kim was an acclaimed American costume designer known for her vibrant, innovative work on Broadway, ballet, and opera, earning multiple Tony Awards over her career.
-
C.
Julia Cho
Julia Cho is an American playwright and screenwriter known for her work on stage and in film, including co-writing Pixar’s animated feature "Turning Red."
-
D.
Julie Oh
Julie Oh is a film producer known for her work on projects such as the musical drama "Tick, Tick... Boom!" (2021).
-
E.
Christina Oh
Christina Oh is an American film producer best known for her work on acclaimed independent films, including the Oscar-nominated drama "Minari."
- F. None of above. chosen
Statements (10)
| Predicate | Object |
|---|---|
| instanceOf |
actress
ⓘ
human ⓘ |
| activeIn | 21st century ⓘ |
| countryOfCitizenship | United States of America ⓘ |
| genre | film acting ⓘ |
| knownFor | role in the film Minari ⓘ |
| languageSpoken | English ⓘ |
| notableWork | Minari NERFINISHED ⓘ |
| occupation | actress ⓘ |
| workLocation | United States of America ⓘ |
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: Noel Kate Cho Description of subject: Noel Kate Cho is a young actress best known for her role in the acclaimed film "Minari."
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.