Triple
T22033539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drishyam 2 |
E544144
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Devi Sri Prasad |
—
|
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: Devi Sri Prasad | Statement: [Drishyam 2, musicBy, Devi Sri Prasad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Devi Sri Prasad Context triple: [Drishyam 2, musicBy, Devi Sri Prasad]
-
A.
Devi Sri Prasad
chosen
Devi Sri Prasad is a prominent Indian film composer and music director best known for his energetic and chart-topping soundtracks in Telugu and other South Indian cinema.
-
B.
Trivikram Srinivas
Trivikram Srinivas is a prominent Indian film director and screenwriter known for his witty dialogues and successful Telugu-language films.
-
C.
Prashanth Neel
Prashanth Neel is an Indian film director and screenwriter best known for helming the blockbuster Kannada-language "KGF" franchise.
-
D.
Dil Raju
Dil Raju is a prominent Indian film producer and distributor known for backing numerous successful and influential Telugu-language movies.
-
E.
Shreyas Talpade
Shreyas Talpade is an Indian film and television actor known for his work in Hindi and Marathi cinema, including notable roles in films like "Iqbal" and various popular comedies.
- 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.