Triple
T21944548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunday |
E541901
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Arjun 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: Arjun Kapoor | Statement: [Gunday, castMember, Arjun Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arjun Kapoor Context triple: [Gunday, castMember, Arjun Kapoor]
-
A.
Arjun Kapoor
chosen
Arjun Kapoor is an Indian film actor known for his work in Bollywood movies such as "Ishaqzaade," "2 States," and "Gunday."
-
B.
Zain Kapoor
Zain Kapoor is the son of Indian Bollywood actor Shahid Kapoor and his wife Mira Rajput Kapoor.
-
C.
Tusshar Kapoor
Tusshar Kapoor is an Indian film actor and producer known for his work in Bollywood comedies such as the "Golmaal" series.
-
D.
Prateik Babbar
Prateik Babbar is an Indian film actor known for his roles in Hindi cinema, including his debut in "Jaane Tu... Ya Jaane Na."
-
E.
Varun Dhawan
Varun Dhawan is a popular Indian film actor known for his work in contemporary Bollywood cinema, particularly in commercial comedies and dramas.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.