Tiffany Haddish
E332986
Tiffany Haddish is an American stand-up comedian and actress known for her breakout role in "Girls Trip" and her energetic, unfiltered comedic style.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Tiffany Haddish canonical | 25 |
| 2018 – Tiffany Haddish | 1 |
| Tiffany Sara Cornilia Haddish | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3143351 — 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: Tiffany Haddish Context triple: [Regina Hall, hasWorkedWith, Tiffany Haddish]
-
A.
Regina Hall
Regina Hall is an American actress and comedian known for her roles in films such as the Scary Movie series, Girls Trip, and numerous television comedies.
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B.
Issa Rae
Issa Rae is an American actress, writer, and producer best known for creating and starring in the HBO series "Insecure."
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C.
Melissa McCarthy
Melissa McCarthy is an American actress and comedian known for her breakout comedic role in "Bridesmaids" and subsequent work in film and television.
-
D.
Sanaa Chappelle
Sanaa Chappelle is an American child actress best known for appearing alongside her father, comedian Dave Chappelle, in the film "A Star Is Born" (2018).
-
E.
Sarah Silverman
Sarah Silverman is an American stand-up comedian, actress, and writer known for her sharp, provocative humor and appearances in film and television.
- 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: Tiffany Haddish Target entity description: Tiffany Haddish is an American stand-up comedian and actress known for her breakout role in "Girls Trip" and her energetic, unfiltered comedic style.
-
A.
Regina Hall
Regina Hall is an American actress and comedian known for her roles in films such as the Scary Movie series, Girls Trip, and numerous television comedies.
-
B.
Issa Rae
Issa Rae is an American actress, writer, and producer best known for creating and starring in the HBO series "Insecure."
-
C.
Melissa McCarthy
Melissa McCarthy is an American actress and comedian known for her breakout comedic role in "Bridesmaids" and subsequent work in film and television.
-
D.
Sanaa Chappelle
Sanaa Chappelle is an American child actress best known for appearing alongside her father, comedian Dave Chappelle, in the film "A Star Is Born" (2018).
-
E.
Sarah Silverman
Sarah Silverman is an American stand-up comedian, actress, and writer known for her sharp, provocative humor and appearances in film and television.
- 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: Tiffany Haddish Description of subject: Tiffany Haddish is an American stand-up comedian and actress known for her breakout role in "Girls Trip" and her energetic, unfiltered comedic style.
Referenced by (27)
Full triples — surface form annotated when it differs from this entity's canonical label.