Ashok Saraf
E551031
Ashok Saraf is a veteran Indian actor and comedian best known for his prolific work in Marathi films and theatre, as well as memorable roles in Hindi cinema and television.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Ashok Saraf canonical | 1 |
Statements (56)
| Predicate | Object |
|---|---|
| instanceOf |
Indian actor
ⓘ
comedian ⓘ human ⓘ stage actor ⓘ television actor ⓘ |
| activeYearsStart | 1960s ⓘ |
| birthDate | 1947-06-04 ⓘ |
| birthPlace |
Bombay Presidency
NERFINISHED
ⓘ
British India ⓘ Mumbai NERFINISHED ⓘ |
| countryOfCitizenship | India ⓘ |
| ethnicGroup | Marathi people NERFINISHED ⓘ |
| familyName | Saraf NERFINISHED ⓘ |
| fieldOfWork |
Hindi cinema
NERFINISHED
ⓘ
Marathi cinema ⓘ Marathi theatre ⓘ television comedy ⓘ |
| gender | male ⓘ |
| genre |
comedy
ⓘ
drama ⓘ |
| givenName | Ashok NERFINISHED ⓘ |
| languageOfWorkOrName |
Hindi
ⓘ
Marathi ⓘ |
| name | Ashok Saraf NERFINISHED ⓘ |
| notableAward |
Filmfare Award Marathi
NERFINISHED
ⓘ
Maharashtra State Film Award NERFINISHED ⓘ |
| notableRole | Anand Mathur in Hum Paanch ⓘ |
| notableWork |
Aamhi Doghe Raja Rani
NERFINISHED
ⓘ
Aayatya Gharat Gharoba NERFINISHED ⓘ Ashi Hi Banwa Banwi NERFINISHED ⓘ Ashihi Banwa Banwi (stage play adaptation) NERFINISHED ⓘ Aunty No. 1 NERFINISHED ⓘ Bhutacha Bhau NERFINISHED ⓘ Changu Mangu NERFINISHED ⓘ Dhum Dhadaka NERFINISHED ⓘ Ek Daav Bhutacha NERFINISHED ⓘ Gammat Jammat NERFINISHED ⓘ Hum Paanch NERFINISHED ⓘ Joru Ka Ghulam NERFINISHED ⓘ Karan Arjun NERFINISHED ⓘ Khatta Meetha (2010 film) NERFINISHED ⓘ Koyla NERFINISHED ⓘ Kunku NERFINISHED ⓘ Navra Mazha Navsacha NERFINISHED ⓘ Pandu Hawaldar NERFINISHED ⓘ Pyaar Kiya To Darna Kya NERFINISHED ⓘ Pyaar To Hona Hi Tha NERFINISHED ⓘ Saatchya Aat Gharat NERFINISHED ⓘ Shubha Bol Narya NERFINISHED ⓘ Singham NERFINISHED ⓘ Yes Boss NERFINISHED ⓘ |
| occupation |
actor
ⓘ
comedian ⓘ |
| partner | Nivedita Joshi-Saraf NERFINISHED ⓘ |
| residence | Mumbai NERFINISHED ⓘ |
| spouse | Nivedita Joshi-Saraf NERFINISHED ⓘ |
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: Ashok Saraf Description of subject: Ashok Saraf is a veteran Indian actor and comedian best known for his prolific work in Marathi films and theatre, as well as memorable roles in Hindi cinema and television.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.