Triple

T20006766
Position Surface form Disambiguated ID Type / Status
Subject Electric Dreams E494479 entity
Predicate hasExecutiveProducer P7225 FINISHED
Object Mona Qureshi NE NERFINISHED

How this triple was built (2 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: Mona Qureshi | Statement: [Electric Dreams, hasExecutiveProducer, Mona Qureshi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mona Qureshi
Context triple: [Electric Dreams, hasExecutiveProducer, Mona Qureshi]
  • A. Mona Qureshi chosen
    Mona Qureshi is a television producer known for her work on high-profile British drama series, including the 2018 adaptation of Les Misérables.
  • B. Moneeza Hashmi
    Moneeza Hashmi is a Pakistani television producer and media professional known for her contributions to public broadcasting and cultural programming.
  • C. Nafisa Ali
    Nafisa Ali is an Indian actress, former Miss India, and social activist known for her roles in Hindi cinema and her work in public life.
  • D. Salma Lakhani
    Salma Lakhani is a Canadian businesswoman and philanthropist who became the first Muslim and first South Asian to serve as a lieutenant governor in Canada.
  • E. Nida Manzoor
    Nida Manzoor is a British screenwriter and director known for her sharp, music-driven comedy and representation of Muslim women, most prominently in her work on the series "We Are Lady Parts."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a648a88190853ee741edcf6ca2 completed April 20, 2026, 5:25 p.m.
Created at: April 11, 2026, 3:33 p.m.