Triple
T11240895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mona Kapoor |
E266069
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Boney Kapoor |
E262553
|
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: Boney Kapoor | Statement: [Mona Kapoor, spouse, Boney Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boney Kapoor Context triple: [Mona Kapoor, spouse, Boney Kapoor]
-
A.
Boney Kapoor
chosen
Boney Kapoor is a prominent Indian film producer known for backing numerous successful Bollywood and South Indian films.
-
B.
Annu Kapoor
Annu Kapoor is an Indian film and television actor, radio host, and television presenter known for his character roles and work on shows like "Antakshari."
-
C.
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.
-
D.
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.
-
E.
Kapoor
Kapoor is a common Indian surname associated with a prominent Punjabi Khatri family, many of whose members have achieved fame in fields such as film, art, and business.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e919eaf48190a1457851cfc56afb |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef81c65ba48190a8e2b9d7078cd978 |
completed | April 27, 2026, 3:33 p.m. |
Created at: April 8, 2026, 9:30 p.m.