Triple

T11102850
Position Surface form Disambiguated ID Type / Status
Subject Boney Kapoor E262553 entity
Predicate spouse P13 FINISHED
Object Mona Shourie Kapoor E266069 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: Mona Shourie Kapoor | Statement: [Boney Kapoor, spouse, Mona Shourie Kapoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mona Shourie Kapoor
Context triple: [Boney Kapoor, spouse, Mona Shourie Kapoor]
  • A. Mona Kapoor chosen
    Mona Kapoor was an Indian television and film producer best known as the first wife of Bollywood film producer Boney Kapoor and mother of actor Arjun Kapoor.
  • B. Ramsarni Mehra Kapoor
    Ramsarni Mehra Kapoor was the wife of pioneering Indian actor and filmmaker Prithviraj Kapoor and matriarch of the influential Kapoor family in Hindi cinema.
  • C. Kumud Mishra
    Kumud Mishra is an Indian film and theatre actor known for his versatile supporting roles in Hindi cinema, including notable performances in movies like Rockstar, Airlift, and Article 15.
  • D. Chitra Singh
    Chitra Singh is an acclaimed Indian ghazal singer, best known for her soulful duets with her late husband Jagjit Singh and for popularizing modern ghazal music.
  • E. Sarita Khurana
    Sarita Khurana is a filmmaker and producer known for her work on culturally focused, immigrant-centered stories in film and television.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a2c30a481908c45020c37caebe4 completed April 9, 2026, 12:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4acd76d20819089ed2ea2c22bc65d completed April 19, 2026, 10:22 a.m.
Created at: April 8, 2026, 9:27 p.m.