Triple

T13667561
Position Surface form Disambiguated ID Type / Status
Subject Citizen Khan E327660 entity
Predicate starring P1507 FINISHED
Object Maya Sondhi
Maya Sondhi is a British actress and writer known for her roles in television comedies and dramas, including the BBC sitcom Citizen Khan and the crime series Line of Duty.
E1052684 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Maya Sondhi | Statement: [Citizen Khan, starring, Maya Sondhi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maya Sondhi
Context triple: [Citizen Khan, starring, Maya Sondhi]
  • A. Annet Mahendru
    Annet Mahendru is an American actress best known for her acclaimed role as Nina Sergeevna Krilova on the television series "The Americans."
  • B. Anjana Patel
    Anjana Patel is a member of a specific subgroup within the broader Patel community, traditionally associated with agrarian and mercantile occupations in India.
  • C. Shefali Chowdhury
    Shefali Chowdhury is a British actress best known for playing Parvati Patil in the Harry Potter film series.
  • D. Maya Bhaskar
    Maya Bhaskar is the daughter of British comedian, writer, and actress Meera Syal.
  • E. Sukanya Rajan
    Sukanya Rajan is the widow of legendary Indian sitar virtuoso Ravi Shankar and the mother of musician Anoushka Shankar.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Maya Sondhi
Triple: [Citizen Khan, starring, Maya Sondhi]
Generated description
Maya Sondhi is a British actress and writer known for her roles in television comedies and dramas, including the BBC sitcom Citizen Khan and the crime series Line of Duty.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maya Sondhi
Target entity description: Maya Sondhi is a British actress and writer known for her roles in television comedies and dramas, including the BBC sitcom Citizen Khan and the crime series Line of Duty.
  • A. Annet Mahendru
    Annet Mahendru is an American actress best known for her acclaimed role as Nina Sergeevna Krilova on the television series "The Americans."
  • B. Anjana Patel
    Anjana Patel is a member of a specific subgroup within the broader Patel community, traditionally associated with agrarian and mercantile occupations in India.
  • C. Shefali Chowdhury
    Shefali Chowdhury is a British actress best known for playing Parvati Patil in the Harry Potter film series.
  • D. Maya Bhaskar
    Maya Bhaskar is the daughter of British comedian, writer, and actress Meera Syal.
  • E. Sukanya Rajan
    Sukanya Rajan is the widow of legendary Indian sitar virtuoso Ravi Shankar and the mother of musician Anoushka Shankar.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65832688190aea688fee0a7cbdb completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78b0cfe0c8190b0fe50931e9788cf completed May 3, 2026, 5:51 p.m.
NEDg Description generation batch_69f78bd727048190a57a75294a9ab53d completed May 3, 2026, 5:54 p.m.
NED2 Entity disambiguation (via description) batch_69f78c94da6c8190b9bc1d04cee19c3c completed May 3, 2026, 5:57 p.m.
Created at: April 9, 2026, 9:52 p.m.