Daniel Wu
E317573
Daniel Wu is a Hong Kong-American actor, director, and producer known for his roles in action and fantasy films as well as the TV series "Into the Badlands."
All labels observed (2)
| Label | Occurrences |
|---|---|
| Daniel Wu canonical | 6 |
| Daniel Wu Yin-cho | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3009839 — 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: Daniel Wu Context triple: [Warcraft, castMember, Daniel Wu]
-
A.
Haifan Lin
Haifan Lin is a prominent stem cell and developmental biologist known for his pioneering research on germline stem cells and RNA regulation.
-
B.
Chang Chen
Chang Chen is a Taiwanese actor known for his roles in acclaimed films such as "Crouching Tiger, Hidden Dragon," "Happy Together," and various international productions.
-
C.
James Hong
James Hong is a prolific American character actor and voice actor known for his roles in films like "Big Trouble in Little China," "Blade Runner," and numerous animated features.
-
D.
Chow Yun-fat
Chow Yun-fat is a renowned Hong Kong actor celebrated for his charismatic performances in action and drama films such as "A Better Tomorrow" and "Crouching Tiger, Hidden Dragon."
-
E.
Lim Jock Hoi
Lim Jock Hoi is a Bruneian diplomat who served as the 14th Secretary-General of the Association of Southeast Asian Nations (ASEAN).
- 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: Daniel Wu Target entity description: Daniel Wu is a Hong Kong-American actor, director, and producer known for his roles in action and fantasy films as well as the TV series "Into the Badlands."
-
A.
Haifan Lin
Haifan Lin is a prominent stem cell and developmental biologist known for his pioneering research on germline stem cells and RNA regulation.
-
B.
Chang Chen
Chang Chen is a Taiwanese actor known for his roles in acclaimed films such as "Crouching Tiger, Hidden Dragon," "Happy Together," and various international productions.
-
C.
James Hong
James Hong is a prolific American character actor and voice actor known for his roles in films like "Big Trouble in Little China," "Blade Runner," and numerous animated features.
-
D.
Chow Yun-fat
Chow Yun-fat is a renowned Hong Kong actor celebrated for his charismatic performances in action and drama films such as "A Better Tomorrow" and "Crouching Tiger, Hidden Dragon."
-
E.
Lim Jock Hoi
Lim Jock Hoi is a Bruneian diplomat who served as the 14th Secretary-General of the Association of Southeast Asian Nations (ASEAN).
- F. None of above. chosen
Statements (49)
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: Daniel Wu Description of subject: Daniel Wu is a Hong Kong-American actor, director, and producer known for his roles in action and fantasy films as well as the TV series "Into the Badlands."
Referenced by (7)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Daniel Wu Yin-cho