Triple
T22755569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neha Kakkar |
E562833
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Sonu Kakkar |
—
|
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: Sonu Kakkar | Statement: [Neha Kakkar, sibling, Sonu Kakkar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sonu Kakkar Context triple: [Neha Kakkar, sibling, Sonu Kakkar]
-
A.
Shekhar Suman
Shekhar Suman is an Indian actor, television host, and comedian known for his work in Hindi films and popular TV shows.
-
B.
Tony Kakkar
chosen
Tony Kakkar is an Indian singer, composer, and music producer known for his work in Hindi pop and Bollywood music.
-
C.
Sonu Nigam
Sonu Nigam is a renowned Indian playback singer and live performer known for his versatile vocals across Bollywood, devotional, and pop music.
-
D.
Kumar Sanu
Kumar Sanu is a renowned Indian playback singer, especially famous for his melodious and prolific contributions to Bollywood film music in the 1990s.
-
E.
Shankar Kistaiya
Shankar Kistaiya was one of the co-conspirators involved in the plot surrounding Narayan Apte, a key figure in the assassination of Mahatma Gandhi.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179bc48788190b3deb9287d02cb2c |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:25 p.m.