Triple

T11535390
Position Surface form Disambiguated ID Type / Status
Subject Randhir Kapoor E273533 entity
Predicate spouse P13 FINISHED
Object Babita Kapoor E911465 NE FINISHED

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: Babita Kapoor | Statement: [Randhir Kapoor, spouse, Babita Kapoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Babita Kapoor
Context triple: [Randhir Kapoor, spouse, Babita Kapoor]
  • A. Babita Kapoor chosen
    Babita Kapoor is an Indian former actress and member of the prominent Kapoor film family, known for her work in Hindi cinema of the late 1960s and 1970s.
  • B. 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.
  • C. 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."
  • 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. Dimple Kapadia
    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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8839b4bb48190b748ec4119f36c11 completed April 10, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6858af0d081909078d5862ec3d469 completed April 20, 2026, 7:59 p.m.
Created at: April 8, 2026, 9:37 p.m.