Triple
T21108653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirzya (2016 film) |
E520118
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Harshvardhan Kapoor |
—
|
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: Harshvardhan Kapoor | Statement: [Mirzya (2016 film), castMember, Harshvardhan Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harshvardhan Kapoor Context triple: [Mirzya (2016 film), castMember, Harshvardhan Kapoor]
-
A.
Harshvardhan Kapoor
chosen
Harshvardhan Kapoor is an Indian film actor known for his work in Hindi cinema, including his debut in the critically acclaimed film "Mirzya."
-
B.
Vikrant Kapoor
Vikrant Kapoor is the central male protagonist in the 1999 Bollywood musical romance film "Taal," portrayed by actor Akshaye Khanna.
-
C.
Kunal Kapoor
Kunal Kapoor is an Indian actor known for his work in Hindi cinema, particularly for his acclaimed performance in the film "Rang De Basanti."
-
D.
Tusshar Kapoor
Tusshar Kapoor is an Indian film actor and producer known for his work in Bollywood comedies such as the "Golmaal" series.
-
E.
Rajat Kapoor
Rajat Kapoor is an Indian actor, writer, and filmmaker known for his work in independent cinema and acclaimed films such as "Bheja Fry," "Mithya," and "Ankhon Dekhi."
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e720ffa998819082db225363ac3b23 |
completed | April 21, 2026, 7:02 a.m. |
Created at: April 16, 2026, 2:54 p.m.