Triple

T19273773
Position Surface form Disambiguated ID Type / Status
Subject Welcome to Sajjanpur E481993 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: [Welcome to Sajjanpur, castMember, Divya Dutta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Divya Dutta
Context triple: [Welcome to Sajjanpur, 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. Kajal Aggarwal
    Kajal Aggarwal is a popular Indian actress best known for her leading roles in Telugu and Tamil cinema, as well as appearances in Hindi films.
  • 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_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fbba7758819081c1c78667c59c5e completed April 20, 2026, 10:11 a.m.
Created at: April 10, 2026, 1:29 p.m.