Triple

T22442103
Position Surface form Disambiguated ID Type / Status
Subject Dev Anand E554776 entity
Predicate workedWith P398 FINISHED
Object Madhubala 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: Madhubala | Statement: [Dev Anand, workedWith, Madhubala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madhubala
Context triple: [Dev Anand, workedWith, Madhubala]
  • A. Madhubala chosen
    Madhubala was a legendary Indian film actress of Hindi cinema’s golden era, celebrated for her beauty, charisma, and iconic performances in classics like "Mughal-e-Azam."
  • B. Meena Kumari
    Meena Kumari was a legendary Indian film actress and poet, celebrated as the "Tragedy Queen" of the Golden Age of Hindi cinema for her intensely emotional and nuanced performances.
  • C. Vyjayanthimala
    Vyjayanthimala is a legendary Indian film actress and Bharatanatyam dancer, celebrated as one of the foremost stars of Hindi cinema’s golden age.
  • D. Smita Patil
    Smita Patil was a critically acclaimed Indian actress known for her powerful performances in parallel cinema during the 1970s and 1980s.
  • E. Saira Banu
    Saira Banu is a celebrated Indian film actress best known for her work in Hindi cinema during the 1960s and 1970s and as the wife of legendary actor Dilip Kumar.
  • 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ae2f7608190b1c1e8bd12ca2162 completed April 29, 2026, 1:12 a.m.
Created at: April 16, 2026, 8:47 p.m.