Laura Dern
E38705
Laura Dern is an acclaimed American actress known for her versatile performances in film and television, including roles in works like "Jurassic Park," "Blue Velvet," and "Big Little Lies."
All labels observed (2)
| Label | Occurrences |
|---|---|
| Laura Dern canonical | 65 |
| Laura Elizabeth Dern | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T292548 — 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: Laura Dern Context triple: [Golden Globe Award for Best Supporting Actress – Motion Picture, notableRecipient, Laura Dern]
-
A.
Jennifer Connelly
Jennifer Connelly is an American actress acclaimed for her versatile performances in films ranging from independent dramas to major Hollywood productions, including her Oscar-winning role in "A Beautiful Mind."
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B.
Michelle Williams
Michelle Williams is an acclaimed American actress known for her emotionally nuanced performances in both independent films and major studio productions, earning multiple Academy Award and Golden Globe nominations and wins.
-
C.
Jodie Foster
Jodie Foster is an acclaimed American actress and filmmaker known for her intense, intelligent performances in films such as "The Silence of the Lambs," "Taxi Driver," and "Contact."
-
D.
Jennifer Ehle
Jennifer Ehle is an award-winning English-American actress known for her acclaimed performances in film, television, and theatre, including her BAFTA-winning role as Elizabeth Bennet in the 1995 BBC adaptation of "Pride and Prejudice."
-
E.
Charlize Theron
Charlize Theron is an Academy Award–winning South African–American actress and producer known for her versatile performances in films such as "Monster," "Mad Max: Fury Road," and "Atomic Blonde."
- 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: Laura Dern Target entity description: Laura Dern is an acclaimed American actress known for her versatile performances in film and television, including roles in works like "Jurassic Park," "Blue Velvet," and "Big Little Lies."
-
A.
Jennifer Connelly
Jennifer Connelly is an American actress acclaimed for her versatile performances in films ranging from independent dramas to major Hollywood productions, including her Oscar-winning role in "A Beautiful Mind."
-
B.
Michelle Williams
Michelle Williams is an acclaimed American actress known for her emotionally nuanced performances in both independent films and major studio productions, earning multiple Academy Award and Golden Globe nominations and wins.
-
C.
Jodie Foster
Jodie Foster is an acclaimed American actress and filmmaker known for her intense, intelligent performances in films such as "The Silence of the Lambs," "Taxi Driver," and "Contact."
-
D.
Jennifer Ehle
Jennifer Ehle is an award-winning English-American actress known for her acclaimed performances in film, television, and theatre, including her BAFTA-winning role as Elizabeth Bennet in the 1995 BBC adaptation of "Pride and Prejudice."
-
E.
Charlize Theron
Charlize Theron is an Academy Award–winning South African–American actress and producer known for her versatile performances in films such as "Monster," "Mad Max: Fury Road," and "Atomic Blonde."
- F. None of above. chosen
Statements (57)
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: Laura Dern Description of subject: Laura Dern is an acclaimed American actress known for her versatile performances in film and television, including roles in works like "Jurassic Park," "Blue Velvet," and "Big Little Lies."
Referenced by (66)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Laura Elizabeth Dern
subject surface form:
Everything Must Go
subject surface form:
Amy Jellicoe