Triple
T5524598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimple Kapadia |
E144890
|
entity |
| Predicate | parentOf |
P120
|
FINISHED |
| Object | Twinkle Khanna |
E528624
|
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: Twinkle Khanna | Statement: [Dimple Kapadia, parentOf, Twinkle Khanna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Twinkle Khanna Context triple: [Dimple Kapadia, parentOf, Twinkle Khanna]
-
A.
Twinkle Khanna
chosen
Twinkle Khanna is an Indian author, columnist, interior designer, and former Bollywood actress known for her witty writing and bestselling books.
-
B.
Kirron Kher
Kirron Kher is an Indian film and television actress and politician known for her powerful character roles in Hindi cinema and her work as a Member of Parliament.
-
C.
Ekta Kapoor
Ekta Kapoor is a prominent Indian television and film producer known for revolutionizing Hindi soap operas and co-founding Balaji Telefilms.
-
D.
Lara Dutta
Lara Dutta is an Indian actress, model, and former Miss Universe (2000) known for her work in Bollywood films.
-
E.
Sonam Kapoor
Sonam Kapoor is a prominent Indian actress and fashion icon known for her work in Hindi cinema and her influential presence in the fashion industry.
- 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_69c008f873a481909b4d9f7e2db3c37d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f874bd081909cccfc25767ee6fa |
completed | March 22, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04cd6ce3c8190ac5ef4c216190266 |
completed | March 22, 2026, 8:11 p.m. |
Created at: March 22, 2026, 3:34 p.m.