Maya Bhaskar
E718198
Maya Bhaskar is the daughter of British comedian, writer, and actress Meera Syal.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Maya Bhaskar canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8189916 — 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: Maya Bhaskar Context triple: [Meera Syal, parentOf, Maya Bhaskar]
-
A.
Janina Gavankar
Janina Gavankar is an American actress and musician known for her roles in television series such as "The L Word," "True Blood," and "The Morning Show," as well as for her work in video games and independent music.
-
B.
Annet Mahendru
Annet Mahendru is an American actress best known for her acclaimed role as Nina Sergeevna Krilova on the television series "The Americans."
-
C.
Karthika Srinivas
Karthika Srinivas is an Indian film editor known for his work in Telugu cinema, including editing the blockbuster film "Pushpa: The Rise."
-
D.
Shailen Mukherjee
Shailen Mukherjee was an Indian actor known for his role in Satyajit Ray’s acclaimed Bengali film "Charulata."
-
E.
Shefali Chowdhury
Shefali Chowdhury is a British actress best known for playing Parvati Patil in the Harry Potter film series.
- 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: Maya Bhaskar Target entity description: Maya Bhaskar is the daughter of British comedian, writer, and actress Meera Syal.
-
A.
Janina Gavankar
Janina Gavankar is an American actress and musician known for her roles in television series such as "The L Word," "True Blood," and "The Morning Show," as well as for her work in video games and independent music.
-
B.
Annet Mahendru
Annet Mahendru is an American actress best known for her acclaimed role as Nina Sergeevna Krilova on the television series "The Americans."
-
C.
Karthika Srinivas
Karthika Srinivas is an Indian film editor known for his work in Telugu cinema, including editing the blockbuster film "Pushpa: The Rise."
-
D.
Shailen Mukherjee
Shailen Mukherjee was an Indian actor known for his role in Satyajit Ray’s acclaimed Bengali film "Charulata."
-
E.
Shefali Chowdhury
Shefali Chowdhury is a British actress best known for playing Parvati Patil in the Harry Potter film series.
- F. None of above. chosen
Statements (10)
| Predicate | Object |
|---|---|
| instanceOf | human ⓘ |
| countryOfCitizenship | United Kingdom ⓘ |
| ethnicGroup | British Indian ⓘ |
| familyName | Bhaskar ⓘ |
| father | Sanjeev Bhaskar ⓘ |
| givenName | Maya ⓘ |
| languageSpoken | English ⓘ |
| mother | Meera Syal ⓘ |
| notableFamilyMember |
Meera Syal
ⓘ
Sanjeev Bhaskar ⓘ |
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: Maya Bhaskar Description of subject: Maya Bhaskar is the daughter of British comedian, writer, and actress Meera Syal.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.