Triple
T22103056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special 26 |
E546216
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Kajal Aggarwal |
—
|
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: Kajal Aggarwal | Statement: [Special 26, starring, Kajal Aggarwal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kajal Aggarwal Context triple: [Special 26, starring, Kajal Aggarwal]
-
A.
Kajal Aggarwal
chosen
Kajal Aggarwal is a popular Indian actress best known for her leading roles in Telugu and Tamil cinema, as well as appearances in Hindi films.
-
B.
Kajal Gupta
Kajal Gupta is an actress known for her work in Tollywood, the Bengali-language film industry based in Kolkata.
-
C.
Meghna Kapoor
Meghna Kapoor is known as the wife of Indian actor and filmmaker Rajat Kapoor.
-
D.
Bela Malhotra
Bela Malhotra is a witty, sex-positive aspiring comedy writer and one of the central student protagonists in the TV series "The Sex Lives of College Girls."
-
E.
Sanah Kapur
Sanah Kapur is an Indian actress known for her supporting role in the film "Shaandaar" and for being part of the Kapur film family.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129175a7881909549883f23c53dca |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.