Triple
T22033549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drishyam 2 |
E544144
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Ajay Devgn |
—
|
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: Ajay Devgn | Statement: [Drishyam 2, stars, Ajay Devgn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ajay Devgn Context triple: [Drishyam 2, stars, Ajay Devgn]
-
A.
Ajay Devgn
chosen
Ajay Devgn is a prominent Indian film actor, director, and producer known for his intense performances in Hindi cinema and his versatility across action, drama, and comedy roles.
-
B.
Akshaye Khanna
Akshaye Khanna is an Indian film actor known for his versatile performances in Hindi cinema across both commercial hits and critically acclaimed dramas.
-
C.
Sunny Deol
Sunny Deol is an Indian film actor, director, and politician best known for his powerful action roles and intense performances in Hindi cinema.
-
D.
Akshay Kumar
Akshay Kumar is a prominent Indian film actor and producer, known for his action and comedy roles in Bollywood and his long-running, commercially successful career.
-
E.
Salman Khan
Salman Khan is an American educator and entrepreneur best known as the founder of the online learning platform Khan Academy.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127ef97348190b8dcdcad11694ebe |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:24 p.m.