Triple
T22103312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Actor Prepares |
E546221
|
entity |
| Predicate | notableAlumni |
P51
|
FINISHED |
| Object | Varun Dhawan |
—
|
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: Varun Dhawan | Statement: [Actor Prepares, notableAlumni, Varun Dhawan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varun Dhawan Context triple: [Actor Prepares, notableAlumni, Varun Dhawan]
-
A.
Varun Dhawan
chosen
Varun Dhawan is a popular Indian film actor known for his work in contemporary Bollywood cinema, particularly in commercial comedies and dramas.
-
B.
Rajkummar Rao
Rajkummar Rao is an acclaimed Indian film actor known for his versatile performances in Hindi cinema, particularly in critically praised independent and mainstream films.
-
C.
Ranbir Kapoor
Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
-
D.
Aditya Sood
Aditya Sood is a film producer known for his work on high-profile Hollywood projects, including the thriller-comedy "Cocaine Bear."
-
E.
Shahid Kapoor
Shahid Kapoor is a popular Indian film actor known for his versatile performances in Hindi cinema, including acclaimed roles in films like "Jab We Met," "Haider," and "Kabir Singh."
- 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.