Triple

T22102910
Position Surface form Disambiguated ID Type / Status
Subject Ram Lakhan E546213 entity
Predicate castMember P1668 FINISHED
Object Dimple Kapadia 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: Dimple Kapadia | Statement: [Ram Lakhan, castMember, Dimple Kapadia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dimple Kapadia
Context triple: [Ram Lakhan, castMember, Dimple Kapadia]
  • A. Dimple Kapadia chosen
    Dimple Kapadia is a renowned Indian film actress known for her work in Hindi cinema since the 1970s, acclaimed for both mainstream and critically lauded roles.
  • B. Asha Parekh
    Asha Parekh is a celebrated Indian film actress and former Bollywood star of the 1960s and 1970s, renowned for her versatile performances and significant contributions to Hindi cinema.
  • C. Shanta Apte
    Shanta Apte was a prominent Indian film actress and playback singer of the 1930s and 1940s, known for her powerful performances in Marathi and Hindi cinema.
  • 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. Shobha Kapoor
    Shobha Kapoor is an Indian television and film producer and the co-founder of Balaji Telefilms, one of India’s leading entertainment production companies.
  • 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_69e11e378dc08190896d6a51597afd5a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129175a7881909549883f23c53dca completed April 28, 2026, 9:39 p.m.
Created at: April 16, 2026, 8:30 p.m.