Triple

T22229749
Position Surface form Disambiguated ID Type / Status
Subject Yash Chopra E549433 entity
Predicate workedWith P398 FINISHED
Object Rekha 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: Rekha | Statement: [Yash Chopra, workedWith, Rekha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rekha
Context triple: [Yash Chopra, workedWith, Rekha]
  • A. Rekha chosen
    Rekha is a celebrated Indian film actress renowned for her versatile performances and enduring impact on Hindi cinema.
  • B. Raakhee
    Raakhee is a renowned Indian film actress known for her acclaimed performances in Hindi and Bengali cinema from the late 1960s through the 1980s.
  • C. Uma Maheswari
    Uma Maheswari is a Hindu goddess venerated as the consort of Lord Shiva and a local deity associated with the town of Sirkazhi in Tamil Nadu, India.
  • D. Nadira Babbar
    Nadira Babbar is an Indian theatre director and actress known for her work in Hindi cinema and on stage, including a role in the film "Bride and Prejudice."
  • E. Rupa Mehra
    Rupa Mehra is a central matriarchal figure in Vikram Seth’s novel "A Suitable Boy," best known for her determined quest to find an ideal husband for her daughter Lata.
  • 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12bf173308190a3d21bfc59b39728 completed April 28, 2026, 9:51 p.m.
Created at: April 16, 2026, 8:37 p.m.