Triple

T22433240
Position Surface form Disambiguated ID Type / Status
Subject Lootera E554548 entity
Predicate castMember P1668 FINISHED
Object Divya Dutta 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: Divya Dutta | Statement: [Lootera, castMember, Divya Dutta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Divya Dutta
Context triple: [Lootera, castMember, Divya Dutta]
  • A. Divya Dutta chosen
    Divya Dutta is an Indian film actress known for her versatile supporting and character roles across Hindi and Punjabi cinema.
  • B. Sanya Malhotra
    Sanya Malhotra is an Indian actress known for her acclaimed debut in the film "Dangal" and subsequent roles in Hindi cinema.
  • C. Priya Dutt
    Priya Dutt is an Indian politician and former Member of Parliament from Mumbai, known for her work with the Indian National Congress and as the daughter of actors-turned-politicians Sunil Dutt and Nargis.
  • D. Divya Katdare
    Divya Katdare is a central character on the television series "Royal Pains," known as a skilled and poised physician assistant who works closely with concierge doctor Hank Lawson in the Hamptons.
  • E. Sonakshi Sinha
    Sonakshi Sinha is an Indian film actress best known for her work in Hindi cinema, including notable performances in both commercial blockbusters and critically acclaimed dramas.
  • 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_69f15a3320448190ae3931062599116e completed April 29, 2026, 1:09 a.m.
Created at: April 16, 2026, 8:47 p.m.